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DDDD Basic Photography in 180 Days Book III - Color Editor: Ramon F. aeroramon.com Contents

1 Day 1 1 1.1 Theory of Colours ...... 1 1.1.1 Historical background ...... 1 1.1.2 Goethe’s theory ...... 2 1.1.3 Goethe’s colour wheel ...... 6 1.1.4 Newton and Goethe ...... 9 1.1.5 History and inﬂuence ...... 10 1.1.6 Quotations ...... 13 1.1.7 See also ...... 13 1.1.8 Notes and references ...... 13 1.1.9 Bibliography ...... 16 1.1.10 External links ...... 16

2 Day 2 18 2.1 Color ...... 18 2.1.1 Physics of color ...... 20 2.1.2 Perception ...... 22 2.1.3 Associations ...... 26 2.1.4 Spectral colors and color reproduction ...... 26 2.1.5 Additive coloring ...... 28 2.1.6 Subtractive coloring ...... 28 2.1.7 Structural color ...... 29 2.1.8 Mentions of color in social media ...... 30 2.1.9 Additional terms ...... 30 2.1.10 See also ...... 30 2.1.11 References ...... 31 2.1.12 External links and sources ...... 31

3 Day 3 32 3.1 Color wheel ...... 32 3.1.1 Colors of the color wheel ...... 33 3.1.2 The color circle and color vision ...... 33 3.1.3 Color wheels and paint color mixing ...... 34

i ii CONTENTS

3.1.4 Color wheel software ...... 34 3.1.5 HSV color wheel ...... 34 3.1.6 Color schemes ...... 34 3.1.7 Gallery ...... 35 3.1.8 See also ...... 35 3.1.9 References ...... 35 3.1.10 External links ...... 36

4 Day 4 41 4.1 Spectral color ...... 41 4.1.1 In color spaces ...... 41 4.1.2 Table of spectral or near-spectral colors ...... 41 4.1.3 Non-spectral colors ...... 42 4.1.4 See also ...... 43 4.1.5 References ...... 43 4.1.6 External links ...... 44 4.2 Color space ...... 44 4.2.1 Examples ...... 44 4.2.2 Conversion ...... 45 4.2.3 RGB density ...... 45 4.2.4 Lists ...... 46 4.2.5 Absolute color space ...... 50 4.2.6 See also ...... 50 4.2.7 References ...... 51 4.2.8 External links ...... 51 4.3 ColorChecker ...... 51 4.3.1 Design ...... 52 4.3.2 Colors ...... 52 4.3.3 Use ...... 52 4.3.4 ColorChecker Digital SG ...... 53 4.3.5 See also ...... 53 4.3.6 References ...... 53 4.3.7 External links ...... 53

5 Day 5 55 5.1 Primary color ...... 55 5.1.1 Biological basis ...... 56 5.1.2 History ...... 57 5.1.3 Examples ...... 57 5.1.4 See also ...... 60 5.1.5 References ...... 60 5.2 Tertiary color ...... 61 CONTENTS iii

5.2.1 RGB or CMY primary, secondary, and tertiary colors ...... 61 5.2.2 Traditional painting (RYB) ...... 61 5.2.3 Comparison of RGB and RYB color wheels ...... 62 5.2.4 See also ...... 62 5.2.5 References ...... 62 5.3 Additive color ...... 66 5.3.1 History ...... 68 5.3.2 Examples ...... 68 5.3.3 See also ...... 69 5.3.4 References ...... 69 5.3.5 External links ...... 70 5.4 Subtractive color ...... 71 5.4.1 RYB ...... 71 5.4.2 CMY and CMYK printing processes ...... 72 5.4.3 See also ...... 73 5.4.4 References ...... 74 5.4.5 External links ...... 74 5.5 Color mixing ...... 75 5.5.1 Additive Mixing ...... 75 5.5.2 Subtractive Mixing ...... 76 5.5.3 See also ...... 77 5.5.4 External links ...... 77 5.5.5 References ...... 78

6 Day 6 79 6.1 Color calibration ...... 79 6.1.1 Information flow and output distortion ...... 79 6.1.2 Color perception ...... 80 6.1.3 Calibration techniques and procedures ...... 80 6.1.4 See also ...... 82 6.1.5 References ...... 83 6.1.6 External links ...... 83 6.2 International Color Consortium ...... 83 6.2.1 ICC profile specification version ...... 83 6.2.2 Membership ...... 83 6.2.3 See also ...... 83 6.2.4 References ...... 84 6.2.5 External links ...... 84 6.3 International Colour Association ...... 84 6.3.1 History ...... 84 6.3.2 Congresses ...... 85 6.3.3 Members and Executive Committee ...... 85 iv CONTENTS

6.3.4 Deane B. Judd Award ...... 85 6.3.5 References ...... 86 6.3.6 External links ...... 86

7 Day 7 87 7.1 Lab color space ...... 87 7.1.1 Advantages ...... 88 7.1.2 Diﬀerentiation ...... 88 7.1.3 CIELAB ...... 88 7.1.4 CIELAB-CIEXYZ conversions ...... 89 7.1.5 Hunter Lab ...... 90 7.1.6 Cylindrical representation: CIELCh or CIEHLC ...... 92 7.1.7 See also ...... 92 7.1.8 References ...... 92 7.1.9 External links ...... 93 7.2 sRGB ...... 98 7.2.1 Background ...... 99 7.2.2 The sRGB gamut ...... 99 7.2.3 The sRGB transfer (gamma) function ...... 99 7.2.4 Speciﬁcation of the transformation ...... 99 7.2.5 Theory of the transformation ...... 101 7.2.6 Viewing environment ...... 102 7.2.7 Usage ...... 102 7.2.8 See also ...... 102 7.2.9 References ...... 102 7.2.10 External links ...... 104 7.3 HSL and HSV ...... 104 7.3.1 Basic principle ...... 105 7.3.2 Motivation ...... 106 7.3.3 Formal derivation ...... 107 7.3.4 Use in end-user software ...... 111 7.3.5 Use in image analysis ...... 111 7.3.6 Disadvantages ...... 112 7.3.7 Other cylindrical-coordinate color models ...... 113 7.3.8 Converting to RGB ...... 114 7.3.9 Swatches ...... 117 7.3.10 Notes and references ...... 117 7.3.11 Bibliography ...... 120 7.3.12 External links ...... 120

8 Day 8 129 8.1 RGB color model ...... 129 CONTENTS v

8.1.1 Additive primary colors ...... 130 8.1.2 Physical principles for the choice of red, green and blue ...... 131 8.1.3 History of RGB color model theory and usage ...... 131 8.1.4 RGB devices ...... 134 8.1.5 Numeric representations ...... 138 8.1.6 Geometric representation ...... 140 8.1.7 Colors in web-page design ...... 140 8.1.8 Color management ...... 141 8.1.9 RGB model and luminance–chrominance formats relationship ...... 142 8.1.10 See also ...... 142 8.1.11 References ...... 142 8.1.12 External links ...... 143 8.2 CMYK color model ...... 143 8.2.1 Halftoning ...... 143 8.2.2 Beneﬁts of using black ink ...... 144 8.2.3 Other printer color models ...... 145 8.2.4 Comparison with RGB displays ...... 145 8.2.5 Conversion ...... 146 8.2.6 See also ...... 146 8.2.7 Notes and references ...... 147 8.2.8 External links ...... 148

9 Day 9 150 9.1 Colorfulness ...... 150 9.1.1 Saturation ...... 151 9.1.2 Excitation purity ...... 153 9.1.3 Chroma in CIE 1976 L*a*b* and L*u*v* color spaces ...... 154 9.1.4 References ...... 154 9.2 Grayscale ...... 155 9.2.1 Numerical representations ...... 155 9.2.2 Converting color to grayscale ...... 155 9.2.3 Grayscale as single channels of multichannel color images ...... 158 9.2.4 See also ...... 158 9.2.5 References ...... 159 9.3 Middle gray ...... 159 9.3.1 History ...... 159 9.3.2 Table of middle grays ...... 159 9.3.3 References ...... 160 9.4 Gray card ...... 160 9.4.1 Application ...... 161 9.4.2 Limitations ...... 162 9.4.3 References ...... 162 vi CONTENTS

9.4.4 See also ...... 162

10 Day 10 163 10.1 List of monochrome and RGB palettes ...... 163 10.1.1 Monochrome palettes ...... 163 10.1.2 Dichrome palettes ...... 165 10.1.3 Regular RGB palettes ...... 165 10.1.4 Non-regular RGB palettes ...... 171 10.1.5 See also ...... 173 10.1.6 Notes ...... 173 10.1.7 External links and sources ...... 174 10.2 Impossible color ...... 174 10.2.1 Types ...... 174 10.2.2 Opponent process ...... 175 10.2.3 Real colors ...... 175 10.2.4 Imaginary colors ...... 176 10.2.5 Chimerical colors ...... 176 10.2.6 Claimed evidence for ability to see impossible colors not in the color space ...... 177 10.2.7 See also ...... 178 10.2.8 References ...... 179 10.2.9 Further reading ...... 179 10.2.10 External links ...... 179

11 Text and image sources, contributors, and licenses 180 11.1 Text ...... 180 11.2 Images ...... 186 11.3 Content license ...... 195 Chapter 1

Day 1

1.1 Theory of Colours

Theory of Colours (German: Zur Farbenlehre) is a book by Johann Wolfgang von Goethe about the poet’s views on the nature of colours and how these are perceived by humans. Published in 1810, it contains detailed descriptions of phenomena such as coloured shadows, refraction, and chromatic aberration. The work originated in Goethe’s occupation with painting and mainly exerted an inﬂuence onto the arts (Philipp Otto Runge, J. M. W. Turner, the Pre-Raphaelites, Wassily Kandinsky). Although Goethe’s work was rejected by physicists, a number of philosophers and physicists have concerned themselves with it, including Thomas Johann Seebeck, Arthur Schopenhauer (see: On Vision and Colors), Hermann von Helmholtz, Rudolf Steiner, Ludwig Wittgenstein, Werner Heisenberg, Kurt Gödel, and Mitchell Feigenbaum. Goethe’s book provides a catalogue of how colour is perceived in a wide variety of circumstances, and considers Isaac Newton's observations to be special cases.[2] Unlike Newton, Goethe’s concern was not so much with the analytic treatment of colour, as with the qualities of how phenomena are perceived. Philosophers have come to understand the distinction between the optical spectrum, as observed by Newton, and the phenomenon of human colour perception as presented by Goethe—a subject analyzed at length by Wittgenstein in his exegesis of Goethe in Remarks on Colour.

1.1.1 Historical background

At Goethe’s time, it was generally acknowledged that, as Isaac Newton had shown in his Opticks in 1704, colourless (white) light is split up into its component colours when directed through a prism.[3]

Along with the rest of the world I was convinced that all the colours are contained in the light; no one had ever told me anything diﬀerent, and I had never found the least cause to doubt it, because I had no further interest in the subject.

But how I was astonished, as I looked at a white wall through the prism, that it stayed white! That only where it came upon some darkened area, it showed some colour, then at last, around the window sill all the colours shone... It didn't take long before I knew here was something signiﬁcant about colour to be brought forth, and I spoke as through an instinct out loud, that the Newtonian teachings were false. — Goethe[4]

Goethe’s starting point was the supposed discovery of how Newton erred in the prismatic experiment,[5] and by 1793 Goethe had formulated his arguments against Newton in the essay "Über Newtons Hypothese der diversen Refrangibilität” (“On Newton’s hypothesis of diverse refrangibility”).[6] Yet, by 1794, Goethe had begun to increasingly note the importance of the physiological aspect of colours.[7] As Goethe notes in the historical section, Louis Bertrand Castel had already published a criticism of Newton’s spectral description of prismatic colour in 1740[8] in which he observed that the sequence of colours split by a prism depended on the distance from the prism—and that Newton was looking at a special case.[9]

1 2 CHAPTER 1. DAY 1

Reddish-yellow edges overlap blue-cyan edges to form green.

“Whereas Newton observed the colour spectrum cast on a wall at a fixed distance away from the prism, Goethe observed the cast spectrum on a white card which was progressively moved away from the prism... As the card was moved away, the projected image elongated, gradually assuming an elliptical shape, and the coloured images became larger, finally merging at the centre to produce green. Moving the card farther led to the increase in the size of the image, until finally the spectrum described by Newton in the Opticks was produced... The image cast by the refracted beam was not fixed, but rather developed with increasing distance from the prism. Consequently, Goethe saw the particular distance chosen by Newton to prove the second proposition of the Opticks as capriciously imposed.” (Alex Kentsis, Between Light and Eye)[10]

The theory we set up against this begins with colourless light, and avails itself of outward conditions, to produce coloured phenomena; but it concedes worth and dignity to these conditions. It does not arro- gate to itself developing colours from the light, but rather seeks to prove by numberless cases that colour is produced by light as well as by what stands against it. — Goethe[11]

In the preface to the Theory of Colours, Goethe explained that he tried to apply the principle of polarity, in the work—a proposition that belonged to his earliest convictions and was constitutive of his entire study of nature.[12]

1.1.2 Goethe’s theory Goethe’s theory of the constitution of colours of the spectrum has not proved to be an unsatisfactory theory, rather it really isn't a theory at all. Nothing can be predicted with it. It is, rather a vague schematic outline of the sort we ﬁnd in James's psychology. Nor is there any experimentum crucis which could decide for or against the theory. — Ludwig Wittgenstein, Remarks on Colour, paragraphs 70

It is hard to present Goethe’s “theory”, since he refrains from setting up any actual theory; he says, “its intention is to portray rather than explain” (Scientiﬁc Studies[13]). Instead of setting up models and explanations, Goethe collected specimens—he was responsible for the meteorological collections of Jena University.[14] By the time of his death, he 1.1. THEORY OF COLOURS 3

Castel’s 1740 comparison of Newton’s spectral colour description with his explanation in terms of the interaction of light and dark, which Goethe later developed into his Theory of Colours 4 CHAPTER 1. DAY 1 had amassed over 17,800 minerals in his personal collection—the largest in all of Europe. He took the same approach to colour—instead of narrowing and isolating things to a single 'experimentum crucius’ (or critical experiment that would prove or disprove his theory), he sought to gain as much breadth for his understanding as possible by developing a wide range of interrogations through which he would reveal the essential character of colour—without having to resort to explanations and theories about perceived phenomena such as 'wavelengths’ or 'particles’. “The crux of his color theory is its experiential source: rather than impose theoretical statements, Goethe sought to allow light and color to be displayed in an ordered series of experiments that readers could experience for themselves.” (Seamon, 1998[15]). According to Goethe, “Newton’s error.. was trusting math over the sensations of his eye.” (Jonah Lehrer, 2006).[16] To stay true to the perception without resort to explanation was the essence of Goethe’s method. What he provided was really not so much a theory, as a rational description of colour. For Goethe, “the highest is to understand that all fact is really theory. The blue of the sky reveals to us the basic law of color. Search nothing beyond the phenomena, they themselves are the theory.”[17]

[Goethe] delivered in full measure what was promised by the title of his excellent work: Data for a Theory of Color. They are important, complete, and signiﬁcant data, rich material for a future theory of color. He has not, however, undertaken to furnish the theory itself; hence, as he himself remarks and admits on page xxxix of the introduction, he has not furnished us with a real explanation of the essential nature of color, but really postulates it as a phenomenon, and merely tells us how it originates, not what it is. The physiological colors ... he represents as a phenomenon, complete and existing by itself, without even attempting to show their relation to the physical colors, his principal theme. ... it is really a systematic presentation of facts, but it stops short at this. — Schopenhauer, On Vision and Colors, Introduction

Goethe outlines his method in the essay, The experiment as mediator between subject and object (1772).[18] It under- scores his experiential standpoint. “The human being himself, to the extent that he makes sound use of his senses, is the most exact physical apparatus that can exist.” (Goethe, Scientiﬁc Studies[13])

I believe that what Goethe was really seeking was not a physiological but a psychological theory of colours. — Ludwig Wittgenstein, Culture and Value, MS 112 255:26.11.1931

Light and darkness

Unlike his contemporaries, Goethe didn't see darkness as an absence of light, but rather as polar to and interacting with light; colour resulted from this interaction of light and shadow. For Goethe, light is “the simplest most undivided most homogenous being that we know. Confronting it is the darkness” (Letter to Jacobi).

...they maintained that shade is a part of light. It sounds absurd when I express it; but so it is: for they said that colours, which are shadow and the result of shade, are light itself. — Johann Eckermann, Conversations of Goethe, entry: January 4, 1824; trans. Wallace Wood

Based on his experiments with turbid media, Goethe characterized colour as arising from the dynamic interplay of darkness and light. Rudolf Steiner, the science editor for the Kurschner edition of Goethe’s works, gave the following analogy:

Modern natural science sees darkness as a complete nothingness. According to this view, the light which streams into a dark space has no resistance from the darkness to overcome. Goethe pictures to himself that light and darkness relate to each other like the north and south pole of a magnet. The darkness can weaken the light in its working power. Conversely, the light can limit the energy of the darkness. In both cases color arises. — Rudolf Steiner, 1897[19] 1.1. THEORY OF COLOURS 5

Goethe expresses this more succinctly:[20]

Yellow is a light which has been dampened by darkness; Blue is a darkness weakened by light.

Experiments with turbid media The action of turbid media was to Goethe the ultimate fact—the Urphänomen—of the world of colours. — John Tyndall, 1880[21]

Goethe’s studies of colour began with experiments which examined the eﬀects of turbid media, such as air, dust, and moisture on the perception of light and dark. The poet observed that light seen through a turbid medium appears yellow, and darkness seen through an illuminated medium appears blue.

The highest degree of light, such as that of the sun... is for the most part colourless. This light, however, seen through a medium but very slightly thickened, appears to us yellow. If the density of such a medium be increased, or if its volume become greater, we shall see the light gradually assume a yellow-red hue, which at last deepens to a ruby colour. If on the other hand darkness is seen through a semi-transparent medium, which is itself illumined by a light striking on it, a blue colour appears: this becomes lighter and paler as the density of the medium is increased, but on the contrary appears darker and deeper the more transparent the medium becomes: in the least degree of dimness short of absolute transparence, always supposing a perfectly colourless medium, this deep blue approaches the most beautiful violet. — Goethe, Theory of Colours, pp. 150–151

He then proceeds with numerous experiments, systematically observing the eﬀects of rareﬁed mediums such as dust, air, and moisture on the perception of colour.

Boundary conditions

When looked at through a prism, the colours seen at a light–dark boundary depend upon the orientation of this light–dark boundary.

When viewed through a prism, the orientation of a light–dark boundary with respect to the prism’s axis is signiﬁcant. With white above a dark boundary, we observe the light extending a blue-violet edge into the dark area; whereas dark above a light boundary results in a red-yellow edge extending into the light area. 6 CHAPTER 1. DAY 1

Goethe was intrigued by this diﬀerence. He felt that this arising of colour at light–dark boundaries was fundamental to the creation of the spectrum (which he considered to be a compound phenomenon). Varying the experimental conditions by using diﬀerent shades of grey shows that the intensity of coloured edges increases with boundary contrast.

Light and dark spectra

Light and dark spectra—when coloured edges overlap in a light spectrum, green results; when they overlap in a dark spectrum, magenta results. (Click for animation)

Since the colour phenomenon relies on the adjacency of light and dark, there are two ways to produce a spectrum: with a light beam in a dark room, and with a dark beam (i.e., a shadow) in a light room. Goethe recorded the sequence of colours projected at various distances from a prism for both cases (see Plate IV, Theory of Colours). In both cases, he found that the yellow and blue edges remain closest to the side which is light, and red and violet edges remain closest to the side which is dark. At a certain distance, these edges overlap—and we obtain Newton’s spectrum. When these edges overlap in a light spectrum, green results; when they overlap in a dark spectrum, magenta results. With a light spectrum (i.e. a shaft of light in a surrounding darkness), we find yellow-red colours along the top edge, and blue-violet colours along the bottom edge. The spectrum with green in the middle arises only where the blue-violet edges overlap the yellow-red edges. With a dark spectrum (i.e., a shadow surrounded by light), we find violet-blue along the top edge, and red-yellow along the bottom edge—and where these edges overlap, we find (extraspectral) magenta.

1.1.3 Goethe’s colour wheel

Further information: Color wheel

When the eye sees a colour it is immediately excited and it is its nature, spontaneously and of necessity, at once to produce another, which with the original colour, comprehends the whole chromatic scale. 1.1. THEORY OF COLOURS 7

Goethe’s symmetric colour wheel with associated symbolic qualities (1809) 8 CHAPTER 1. DAY 1

— Goethe, Theory of Colours

Goethe anticipated Ewald Hering's Opponent process theory[22] by proposing a symmetric colour wheel. He writes, “The chromatic circle... [is] arranged in a general way according to the natural order... for the colours diametrically opposed to each other in this diagram are those which reciprocally evoke each other in the eye. Thus, yellow demands violet; orange [demands] blue; purple [demands] green; and vice versa: thus... all intermediate gradations reciprocally evoke each other; the simpler colour demanding the compound, and vice versa ([23] paragraph #50). In the same way that light and dark spectra yielded green from the mixture of blue and yellow—Goethe completed his colour wheel by recognising the importance of magenta—"For Newton, only spectral colors could count as fundamental. By contrast, Goethe’s more empirical approach led him to recognize the essential role of magenta in a complete color circle, a role that it still has in all modern color systems.”[2]

Complementary colours and colours psychology

The “rose of temperaments” (Temperamentenrose), an earlier study (1798/9) by Goethe and Schiller, matching twelve colours to human occupations or their character traits (tyrants, heroes, adventurers, hedonists, lovers, poets, public speakers, historians, teachers, philosophers, pedants, rulers), grouped in the four temperaments.

Goethe also included aesthetic qualities in his colour wheel, under the title of “allegorical, symbolic, mystic use of 1.1. THEORY OF COLOURS 9

colour” (Allegorischer, symbolischer, mystischer Gebrauch der Farbe), establishing a kind of color psychology. He associated red with the “beautiful”, orange with the “noble”, yellow to the “good”, green to the “useful”, blue to the “common”, and violet to the “unnecessary”. These six qualities were assigned to four categories of human cognition, the rational (Vernunft) to the beautiful and the noble (red and orange), the intellectual (Verstand) to the good and the useful (yellow and green), the sensual (Sinnlichkeit) to the useful and the common (green and blue) and, closing the circle, imagination (Phantasie) to both the unnecessary and the beautiful (purple and red).[24]

Notes on translation Magenta appeared as a colour term only in the mid-nineteenth century, after Goethe. Hence, references to Goethe’s recognition of magenta are fraught with interpretation. If one observes the colours coming out of a prism—an English person may be more inclined to describe as magenta what in German is called Purpur—so one may not lose the intention of the author. However, literal translation is more diﬃcult. Goethe’s work uses two composite words for mixed (intermediate) hues along with corresponding usual colour terms such as “orange” and “violet”. It is not clear how Goethe’s Rot, Purpur (explicitly named as the complementary to green),[23] and Schön (one of the six colour sectors) are related between themselves and to the red tip of the visible spectrum. The text about interference from the “physical” chapter[25] does not consider Rot and Purpur synonymous. Also, Purpur is certainly distinct from Blaurot, because Purpur is named as a colour which lies somewhere between Blaurot and Gelbrot (,[25] paragraph 476), although possibly not adjacent to the latter. This article uses the English translations from the above table.

1.1.4 Newton and Goethe

“The essential difference between Goethe’s theory of colour and the theory which has prevailed in science (despite all modifications) since Newton’s day, lies in this: While the theory of Newton and his successors was based on excluding the colour-seeing faculty of the eye, Goethe founded his theory on the eye’s experience of colour.”[26] “The renouncing of life and immediacy, which was the premise for the progress of natural science since Newton, formed the real basis for the bitter struggle which Goethe waged against the physical optics of Newton. It would be superficial to dismiss this struggle as unimportant: there is much significance in one of the most outstanding men directing all his efforts to fighting against the development of Newtonian optics.” (Werner Heisenberg, during a speech celebrating Goethe’s birthday)[27] Due to their different approaches to a common subject, many misunderstandings have arisen between Newton’s mathematical understanding of optics, and Goethe’s experiential approach.[28] Because Newton understands white light to be composed of individual colours, and Goethe sees colour arising from the interaction of light and dark, they come to different conclusions on the question: is the optical spectrum a primary or a compound phenomenon? For Newton, the prism is immaterial to the existence of colour, as all the colours already exist in white light, and the prism merely fans them out according to their refrangibility. Goethe sought to show that, as a turbid medium, the prism was an integral factor in the arising of colour. Whereas Newton narrowed the beam of light in order to isolate the phenomenon, Goethe observed that with a wider aperture, there was no spectrum. He saw only reddish-yellow edges and blue-cyan edges with white between them, and the spectrum arose only where these edges came close enough to overlap. For him, the spectrum could be explained by the simpler phenomena of colour arising from the interaction of light and dark edges. Newton explains the appearance of white with colored edges by saying that due to the differing overall amount of refraction, the rays mix together to create a full white towards the centre, whereas the edges do not benefit from this full mixture and appear with greater red or blue components. For Newton’s account of his experiments, see his Opticks (1704).[29]

Table of diﬀerences

Goethe’s reiﬁcation of darkness is rejected by modern physics. Both Newton and Huygens deﬁned darkness as an absence of light. Young and Fresnel combined Newton’s particle theory with Huygen’s wave theory to show that colour is the visible manifestation of light’s wavelength. Physicists today attribute both a corpuscular and undulatory character to light—comprising the wave–particle duality. 10 CHAPTER 1. DAY 1

1.1.5 History and inﬂuence

The ﬁrst edition of the Farbenlehre was printed at the Cotta’schen Verlagsbuchhandlung on May 16, 1810, with 250 copies on grey paper and 500 copies on white paper. It contained three sections: i) a didactic section in which Goethe presents his own observations, ii) a polemic section in which he makes his case against Newton, and iii) a historical section. From its publication, the book was controversial for its stance against Newton. So much so, that when Charles Eastlake translated the text into English in 1840, he omitted the content of Goethe’s polemic against Newton.

Signiﬁcantly (and regrettably), only the 'Didactic' colour observations appear in Eastlake’s translation. In his preface, Eastlake explains that he deleted the historical and entoptic parts of the book because they 'lacked scientiﬁc interest', and censored Goethe’s polemic because the 'violence of his objections’ against Newton would prevent readers from fairly judging Goethe’s color observations. — Bruce MacEvoy, Handprint.com, 2008[30]

Inﬂuence on the arts

Turner’s The ﬁghting Temeraire, 1839

Goethe was initially induced to occupy himself with the study of colour by the questions of hue in painting. “During his ﬁrst journey to Italy (1786–88), he noticed that artists were able to enunciate rules for virtually all the elements of painting and drawing except color and coloring. In the years 1786–88, Goethe began investigating whether one could ascertain rules to govern the artistic use of color.”[31] This aim came to some fulﬁllment when several pictorial artists, above all Philipp Otto Runge, took an interest in his colour studies.[32] After being translated into English by Charles Eastlake in 1840, the theory became widely adopted by the art world—especially among the Pre-Raphaelites. J. M. W. Turner studied it comprehensively and referenced it in the titles of several paintings.[33] Wassily Kandinsky considered it “one of the most important works.”[34] 1.1. THEORY OF COLOURS 11

Inﬂuence on Latin American ﬂags

Flag of Colombia

During a party in Weimar in the winter of 1785, Goethe had a late-night conversation on his theory of primary colours with the South American revolutionary Francisco de Miranda. This conversation inspired Miranda, as he later recounted, in his designing the yellow, blue and red ﬂag of Gran Colombia, from which the present national ﬂags of Colombia, Venezuela and Ecuador are derived. (See Flag of Colombia#History.)

Inﬂuence on philosophers

In the nineteenth century Goethe’s Theory was taken up by Schopenhauer in On Vision and Colors, who developed it into a kind of arithmetical physiology of the action of the retina, much in keeping with his own representative realism. In the twentieth century the theory was transmitted to philosophy via Wittgenstein, who devoted a series of remarks to the subject at the end of his life. These remarks are collected as Remarks on Colour, (Wittgenstein, 1977).

Someone who agrees with Goethe ﬁnds that Goethe correctly recognized the nature of colour. And here ‘nature’ does not mean a sum of experiences with respect to colours, but it is to be found in the concept of colour. — Aphorism 125, Ludwig Wittgenstein, Remarks on Color, 1992[35]

Wittgenstein was interested in the fact that some propositions about colour are apparently neither empirical nor exactly a priori, but something in between: phenomenology, according to Goethe. However, he took the line that 'There is no such thing as phenomenology, though there are phenomenological problems.' He was content to regard Goethe’s observations as a kind of logic or geometry. Wittgenstein took his examples from the Runge letter included in the “Farbenlehre”, e.g. “White is the lightest colour”, “There cannot be a transparent white”, “There cannot be a reddish green”, and so on. The logical status of these propositions in Wittgenstein’s investigation, including their relation to physics, was discussed in Jonathan Westphal’s Colour: a Philosophical Introduction (Westphal, 1991). 12 CHAPTER 1. DAY 1

Reception by scientists

As early as 1853, in Hermann von Helmholtz's lecture on Goethe’s scientific works—he says of Goethe’s work that he depicts the perceived phenomena—"circumstantially, rigorously true to nature, and vividly, puts them in an order that is pleasant to survey, and proves himself here, as everywhere in the realm of the factual, to be the great master of exposition” (Helmholtz 1892). Helmholtz ultimately rejects Goethe’s theory as the work of a poet, but expresses his perplexity at how they can be in such agreement about the facts of the matter, but in violent contradiction about their meaning—'And I for one do not know how anyone, regardless of what his views about colours are, can deny that the theory in itself is fully consequent, that its assumptions, once granted, explain the facts treated completely and indeed simply'. (Helmholtz 1892)[36] Although the accuracy of Goethe’s observations does not admit a great deal of criticism, his theory’s failure to demonstrate significant predictive validity eventually rendered it scientifically irrelevant. Thomas Johann Seebeck was the only prominent scientist among Goethe’s contemporaries who acknowledged the theory, but later saw it critically.[37]

Goethe’s colour theory has in many ways borne fruit in art, physiology and aesthetics. But victory, and hence inﬂuence on the research of the following century, has been Newton’s. — Werner Heisenberg, 1952

“One hole Goethe did ﬁnd in Newton’s armour, through which he incessantly worried the English- man with his lance. Newton had committed himself to the doctrine that refraction without colour was impossible. He therefore thought that the object-glasses of telescopes must for ever remain imperfect, achromatism and refraction being incompatible. This inference was proved by Dollond to be wrong... Here, as elsewhere, Goethe proves himself master of the experimental conditions. It is the power of interpretation that he lacks.” — John Tyndall, 1880[38]

Much controversy stems from two diﬀerent ways of investigating light and colour. Goethe was not interested in Newton’s analytic treatment of colour—but he presented an excellent rational description of the phenomenon of human colour perception. It is as such a collection of colour observations that we must view this book.

Most of Goethe’s explanations of color have been thoroughly demolished, but no criticism has been leveled at his reports of the facts to be observed; nor should any be. This book can lead the reader through a demonstration course not only in subjectively produced colors (after images, light and dark adaptation, irradiation, colored shadows, and pressure phosphenes), but also in physical phenomena de- tectable qualitatively by observation of color (absorption, scattering, refraction, diﬀraction, polarization, and interference). A reader who attempts to follow the logic of Goethe’s explanations and who attempts to compare them with the currently accepted views might, even with the advantage of 1970 sophistica- tion, become convinced that Goethe’s theory, or at least a part of it, has been dismissed too quickly. — Judd, 1970[39]

Mitchell Feigenbaum came to believe that “Goethe had been right about colour!"[2]

As Feigenbaum understood them, Goethe’s ideas had true science in them. They were hard and empirical. Over and over again, Goethe emphasized the repeatability of his experiments. It was the perception of colour, to Goethe, that was universal and objective. What scientiﬁc evidence was there for a deﬁnable real-world quality of redness independent of our perception? — James Gleick, Chaos[40]

Current status

“Goethe’s critique of Newton was not an attack on reason or science, though it has often been portrayed that way.. The critique maintained that Newton had mistaken mathematical imagining as the pure evidence of the senses.. Goethe 1.1. THEORY OF COLOURS 13 tried to deﬁne the scientiﬁc function of imagination: to interrelate phenomena once they have been meticulously produced, described, and organized... Newton had introduced dogma.. into color science by claiming that color could be reduced to a function of rays.” (Dennis L. Sepper, 2009)[41]

Goethe started out by accepting Newton’s physical theory. He soon abandoned it... finding modification to be more in keeping with his own insights. One beneficial consequence of this was that he developed an awareness of the importance of the physiological aspect of colour perception, and was therefore able to demonstrate that Newton’s theory of light and colours is too simplistic; that there is more to colour than variable refrangibility. — Michael Duck, 1988[42]

As a catalogue of observations, Goethe’s experiments probe the complexities of human colour perception. Whereas Newton sought to develop a mathematical model for the behaviour of light, Goethe focused on exploring how colour is perceived in a wide array of conditions. Developments in understanding how the brain interprets colours, such as colour constancy and Edwin H. Land's retinex theory bear striking similarities to Goethe’s theory.[2] A modern treatment of the book is given by Dennis L. Sepper in the book, Goethe contra Newton: Polemics and the Project for a New Science of Color (Cambridge University Press, 2003).[31]

1.1.6 Quotations

1.1.7 See also

• Checker shadow illusion (Same color illusion) • Color theory • Opponent process • Romanticism in science • Theory of painting

1.1.8 Notes and references

[1] http://findarticles.com/p/articles/mi_m0422/is_2_82/ai_64573524/pg_6. Missing or empty |title= (help)

[2] Neil Ribe, Friedrich Steinle: Exploratory Experimentation: Goethe, Land, and Color Theory. Physics Today, July 2002, retrieved July 3, 2011

[3] Karl Robert Mandelkow: Goethes Briefe (Goethe’s Letters). 2. edition. Vol. 2: Briefe der Jahre 1786–1805 (Letters of the years 1786–1805). Christian Wegner publishers, Hamburg 1968, p. 528. “das zentrale Axiom von Newtons Farbentheorie, daß in dem weißen, farblosen Licht alle Farben enthalten seien” (“the central axiom of Newton’s colour theory that there were all colours in the white, colourless light”)

[4] Goethe, Goethes Werke, Weimar: Hermann Böhlau, 1887–1919, II. Abtheilung: Naturwissenschaftlichte Schriften, Bd. 4, pp. 295–296

[5] Matthaei, Rupprecht. Über die Anfänge von Goethes Farbenlehre (On the beginnings of Goethe’s Theory of Colours). In: Jahrbuch der Goethe-Gesellschaft (Yearbook of the Goethe Society) 11, 1949, p. 259, cited in Karl Robert Mandelkow: Goethes Briefe (Goethe’s Letters). 2. edition. Vol. 2: Briefe der Jahre 1786–1805 (Letters of the years 1786–1805). Christian Wegner publishers, Hamburg 1968, p. 553. “Goethes Ausgangspunkt, die Entdeckung des Newtonschen Irrtums, wie er es nannte, im prismatischen Versuch, schwand ihm aus dem Blickfeld in dem Maße, als er die Bedeutung der Physiologischen Farben zu ahnen begann.” (“Goethe’s starting point, the discovery of the Newton error, as he called it, in the prismatic experiment, dwindled from his horizon according to how he began to sense the meaning of the Physiological Colours.”)

[6] Karl Robert Mandelkow: Goethes Briefe (Goethe’s Letters). 2. edition. Vol. 2: Briefe der Jahre 1786–1805 (Letters of the years 1786–1805). Christian Wegner publishers, Hamburg 1968, p. 528. “Bereits 1793 hat Goethe seine Einwände gegen Newton formuliert in dem Aufsatz Über Newtons Hypothese der diversen Refrangibilität (...).” (“Already in 1793, Goethe formulated his arguments against Newton in the essay Über Newtons Hypothese der diversen Refrangibilität [...].”) 14 CHAPTER 1. DAY 1

[7] Karl Robert Mandelkow: Goethes Briefe (Goethe’s Letters). 2. edition. Vol. 2: Briefe der Jahre 1786–1805 (Letters of the years 1786–1805). Christian Wegner publishers, Hamburg 1968, p. 553. “Diese Wendung ist bereits angedeutet in Goethes Briefentwurf an Sömmerring vom Januar/Februar 1794, der Antwort auf Sömmerrings Brief an Goethe vom 18. Januar 1794 (...): Es ist weit mehr Physiologisches bei den Farbenerscheinungen, als man denkt, nur ist hier die Schwierigkeit noch größer als in andern Fällen, das Objektive vom Subjektiven zu unterscheiden.” (Italics mark citations that may only slightly have been adapted to the descriptive sentence regarding the grammar.) Translation: “This change is already indicated in Goethe’s draft for a letter to Sömmerring from January/February 1794, the answer to Sömmerring’s letter from January 18, 1794 (...): There is much more physiological with the phenomena of colours than one would think, just that it is even more diﬃcult, here, to distinguish between the objective and the subjective.” The letter is cited by Mandelkow after: Goethe, Die Schriften zur Naturwissenschaft. Herausgegeben im Auftrage der Deutschen Akademie der Naturforscher (Leopoldina) zu Halle von R. Matthaei, W. Troll und L. Wolf. Weimar 1949 ﬀ (Goethe, The writings on sciences. Edited on behalf of the German Academy of Sciences Leopoldina at Halle by R. Matthaei, W. Troll and L. Wolf. Weimar 1949 et seq.) See: Samuel Thomas von Sömmerring

[8] Louis-Bertrand Castel (1740). L'Optique des couleurs. Paris.

[9] Thomas L. Hankins and Robert J. Silverman (1995). Instruments and the Imagination. Princeton University Press. ISBN 0-691-00549-4.

[10] http://arxiv.org/pdf/physics/0511130 | Alex Kentsis, Between Light and Eye

[11] Karl Robert Mandelkow: Goethes Briefe (Goethe’s Letters). 2. edition. Vol. 2: Briefe der Jahre 1786–1805 (Letters of the years 1786–1805). Christian Wegner publishers, Hamburg 1968, p. 528. “Die Lehre dagegen, die wir mit Überzeugung aufstellen, beginnt zwar auch mit dem farblosen Lichte, sie bedient sich äußerer Bedingungen, um farbige Erscheinungen hervorzubringen; sie gesteht aber diesen Bedingungen Wert und Würde zu. Sie maßt sich nicht an, Farben aus dem Licht zu entwickeln, sie sucht vielmehr durch unzählige Fälle darzutun, dass die Farbe zugleich von dem Lichte und von dem, was sich ihm entgegenstellt, hervorgebracht werde.”

[12] Karl Robert Mandelkow: Goethes Briefe (Goethe’s Letters). 2. edition. Vol. 2: Briefe der Jahre 1786–1805 (Letters of the years 1786–1805). Christian Wegner publishers, Hamburg 1968, p. 530. “Das für Goethes gesamte Naturbetrachtung konstitutive Prinzip der Polarität gehört zu seinen frühesten Überzeugungen..., an denen er niemals irre geworden sei (Brief an Schweigger, 25. April 1814). Im Vorwort zur Farbenlehre wird es als Hauptabsicht des gegenwärtigen Werkes bezeichnet, dieses universelle Prinzip auch auf die Farbenlehre anzuwenden.” (Italics mark citations that may only slightly have been adapted to the descriptive sentence regarding the grammar.) Translation: “The principle of polarity, that is constitutive for all of Goethe’s study of nature, belongs to the earliest of his convictions..., that he had never lost faith in (letter to Schweigger, April 25, 1814). In the preface to the Theory of Colours, it is called the main intention of the work at hand to apply this universal principle also to the theory of colours.” See Johann Schweigger

[13] Goethe, Johann (October 1995). Miller, Douglas, ed. “Scientiﬁc Studies (Goethe: The Collected Works, Vol. 12), p.57”. Princeton University Press.

[14] E. P. Hamm, Unpacking Goethes Collections: The Public and the Private in Natural-Historical Collecting The British Journal for the History of Science, Vol. 34, No. 3 (Sep., 2001), pp. 275-300, Cambridge University Press,

[15] Seamon, David (1998). Seamon, David; Zajonc, Arthur, eds. Goethe’s Way of Science: A Phenomenology of Nature. Albany, NY: State University of New York Press.

[16] Jonah Lehrer|Goethe and Color, December 7, 2006

[17] Quoted in translation in: Hughes, Peter (1992). “Performing Theory: Wittgenstein and the Trouble with Shakespeare”. Comparative Criticism. 14: 85.

[18] Raymond, Elﬁe. “Faces of Philosophy – Elﬁe Raymond”.

[19] Steiner, Rudolf (1897). Goethe’s World View, Chapter III The Phenomena of the World of Colors.(published in German as Goethe’s Weltanshauung)

[20] Goethe, Johann (1810). Theory of Colours, paragraph #502.

[21] Tyndall, John (1880). Popular Science Monthly, Volume 17, June 1880, Goethe’s Farbenlehre.

[22] Goethe’s Color Theory. Webexhibits.org, retrieved July 3, 2011

[23] Goethe, Johann Wolfgang von (1810). “1. Abteilung. Physiologische Farben”. Zur Farbenlehre [Theory of Colours] (in German). Retrieved 2013-01-21. 1.1. THEORY OF COLOURS 15

[24] Goethe: Farbenkreis zur Symbolisierung des “menschlichen Geistes- und Seelenlebens”. 1809. Goethe und die Kunst. ed. Sabine Schulze. Stuttgart: Hatje 1994, p. 141. “Jeder Farbe wird eine menschliche Eigenschaft zugeordnet (...). Im inneren Ring: rot – 'schön', gelbrot – 'edel', gelb – 'gut', grün – 'nützlich', blau – 'gemein', blaurot – 'unnöthig'.” (“Each colour, a human quality is attributed to [...]. In the inner ring: red – 'beautiful', orange – 'noble', yellow – 'good', green – 'useful', blue – 'mean', violet – 'unnecessary'.”)

[25] Goethe, Johann Wolfgang von (1810). “2. Abteilung. Physische Farben”. Zur Farbenlehre [Theory of Colours] (in German). Retrieved 2013-03-31.

[26] Ernst Lehrs, Man or Matter, retrieved January 10, 2014

[27] Ernst Lehrs, Man or Matter, Chapter II | https://archive.org/stream/manormatter05641gut/elmom10p#page/n23/mode/ 2up

[28] R. H. Stephenson, Goethe’s Conception of Knowledge and Science (Edinburgh: Edinburgh University Press, 1995)

[29] Opticks Or, A treatise of the Reﬂections, Refractions, Inﬂexions and Colours of Light, Also Two treatises of the Species and Magnitude of Curvilinear Figures (London, 1704)

[30] http://www.handprint.com/HP/WCL/goethe.html | Bruce MacEvoy | Handprint.com | 2008

[31] Sepper, Dennis L. | Goethe contra Newton: Polemics and the Project for a New Science of Color | Cambridge University Press | 2007 | ISBN 0-521-53132-2

[32] Karl Robert Mandelkow: Goethes Briefe (Goethe’s Letters). 2. edition. Vol. 4: Briefe der Jahre 1821–1832 (Letters of the years 1821–1832). C. H. Beck publishers, München 1976, p. 622. “Wie die Anfänge von Goethes Beschäftigung mit der Farbenlehre veranlaßt waren durch die Frage nach dem Kolorit in der Malerei (...), so war die Anteilnahme bildender Künstler an seinen Farbenstudien für Goethe eine hochwillkommene Bestätigung des von ihm Gewollten, wie er sie vor allem von Philipp Otto Runge erfahren hat.” (“As the beginnings of Goethe’s occupation with the theory of colours were induced by the question of hue in painting [...], the interest of pictorial artists in his colour studyings was a highly welcome acknowledgement of what he wanted, for him, which he above all received from Philipp Otto Runge.”)

[33] Bockemuhl, M. (1991). Turner. Taschen, Köln. ISBN 3-8228-6325-4.

[34] Rowley, Alison (September–December 2002). “Kandinskii’s theory of colour and Olesha’s Envy”. LookSmart FindArti- cles. Retrieved 2007-07-14.

[35] http://www.homodiscens.com/home/ways/perspicax/color_vision_sub/art_color_theory/ | Ludwig Wittgenstein | Univer- sity of California Press | 1992

[36] Helmholtz, Hermann von. 1892. Goethes Vorahnungen kommender naturwissenschaftlicher Ideen. Berlin: Pastel. 1971. Philosophische Vortrdge und Aufsdtze. Ed. H. Horz and S. Wollgast. Berlin: Akademie-Verlag.

[37] Bodo Morawe: Goethes Briefe (Goethe’s Letters). 1. edition. Vol. 3: Briefe der Jahre 1805–1821 (Letters of the years 1805–1821). Christian Wegner publishers, Hamburg 1965, p. 623. "[Seebeck] ist unter den Zeitgenossen der einzige proﬁlierte Naturwissenschaftler, der Goethes Farbenlehre anerkannte, wenn er sie auch in den letzten Jahren dann kritisch sah.” ("[Seebeck] is the only prominent scientist among the contemporaries who acknowledged Goethe’s Theory of Colours, even though he then saw it critically, in the last years.”)

[38] Popular Science Monthly/Volume 17/July 1880)http://en.wikisource.org/wiki/Popular_Science_Monthly/Volume_17/July_ 1880/Goethe’{}s_Farbenlehre:_Theory_of_Colors_II

[39] Judd, Deane B. (1970). Introduction by Deane B. Judd, Goethe’s Theory of Colours. Cambridge: MIT Press. Retrieved 2007-09-14.

[40] Gleick, James (1988). Chaos, pp. 165-7. London: William Heinemann Publishers.

[41] Sepper, Dennis L. (2009). “Goethe Newton and the Imagination of Modern Science, 2009/3 (n° 249)". Revue internationale de philosophie.

[42] Duck, Michael (September 1988). “Newton and Goethe on colour: Physical and physiological considerations”. Annals of Science, Volume 45, Number 5, pp. 507-519. Retrieved 2011-03-29. 16 CHAPTER 1. DAY 1

1.1.9 Bibliography

• Goethe, Theory of Colours, trans. Charles Lock Eastlake, Cambridge, MA: MIT Press, 1982. ISBN 0-262- 57021-1

• Bockemuhl, M., Turner. Koln: Taschen, 1991. ISBN 3-8228-6325-4.

• Duck, Michael, “Newton and Goethe on colour: Physical and physiological considerations”, Annals of Science 45(5), September 1988. pp. 507–519.

• Gleick, James, Chaos, London: William Heinemann, 1988. pp. 165–7

• Lehrer, Jonah, Goethe and Color, Science Blogs: The Frontal Cortex, 7 Dec. 2006.

• Lehrs, Ernst, Man or Matter, Chapter XIV

• M.W. Rowe, Goethe and Wittgenstein, Philosophy, Vol. 66, No. 257 (Jul., 1991), pp. 283–303, Cambridge University Press JSTOR

• Ribe, Neil and Friedrich Steinle, “Exploratory Experimentation: Goethe, Land, and Color Theory”, Physics Today 55(7), July 2002.

• Proskauer, The Rediscovery of Color, Dornach: Steiner Books, 1986.

• Schopenhauer, On Vision and Colors, Providence: Berg, 1994. ISBN 0-85496-988-8

• Sepper, Dennis L., Goethe contra Newton: Polemics and the Project for a New Science of Color, Cambridge: Cambridge University Press, 2007. ISBN 0-521-53132-2

• Sepper, Dennis L., “Goethe Newton and the Imagination of Modern Science”, Revue internationale de philosophie, 2009/3 (n° 249), 2009.

• Steiner, Rudolf, First Scientiﬁc Lecture-Course, Third Lecture, Stuttgart, 25 December 1919. GA320.

• Steiner, Rudolf, “Goethe’s World View”, Chapter III The Phenomena of the World of Colors, 1897.

• Westphal, Jonathan, “Colour: a Philosophical Introduction”, Aristotelian Society Series, Vol. 7, Oxford, Blackwell, 1991 (2nd. ed.).

• Wittgenstein, Remarks on Colour, Berkeley: University of California Press, 1978. ISBN 0-520-03727-8

1.1.10 External links

• Theory of Colours (German) online pdf

• Theory of Colours (English)

• Theory of Colours (audiobook; released June 2014) (English)

• Physics Today – Exploratory Experimentation: Goethe, Land, and Colour Theory, 2002

• Goethe’s Prismatic Experiments; Fotos by Sakae Tajima

• Light, Darkness and Colour, a ﬁlm by Henrik Boëtius (1998)

• Connections That Have a Quality of Necessity: Goethe’s Way Of Science As a Phenomenology of Nature

• Colour Mixing and Goethe’s Triangle (Java Applet)

• Texts on Wikisource:

• John Tyndall,"Goethe’s Farbenlehre-(Theory of Colors) I", in Popular Science Monthly, Vol. 17, June 1880. • John Tyndall, "Goethe’s Farbenlehre-(Theory of Colors) II", in Popular Science Monthly, Vol. 17, July 1880. 1.1. THEORY OF COLOURS 17

• BBC Radio 4 Podcast, In Our Time Science – Goethe and the Science of the Enlightenment (download free of charge), or this link • Critical review of Goethe’s Theory of Colours

• A list of links relating to Goethe’s investigation of colour • Essay discussing color psychology and Goethe’s theory

• Google Scholar: Works citing Theory of Colours Chapter 2

Day 2

2.1 Color

For other uses of “Color” and “Colour”, see Color (disambiguation). For editing Wikipedia, see Help:Using color. See also, Colorful (disambiguation) and List of colors.

Colored pencils

Color (American English) or colour (Commonwealth English) is the characteristic of human visual perception described through color categories, with names such as red, yellow, purple, or bronze. This perception of color derives from the stimulation of cone cells in the human eye by electromagnetic radiation in the spectrum of light. Color categories and physical specifications of color are associated with objects through the wavelength of the light that is reflected from them. This reflection is governed by the object’s physical properties such as light absorption, emission spectra, etc. Human trichromacy is the basis for all modern color spaces that assign colors numerical coordinates and associate corresponding distances between colors. The photo-receptivity of the “eyes” of other species also varies considerably from our own and so results in pre-

18 2.1. COLOR 19

Color eﬀect – Sunlight shining through stained glass onto carpet (Nasir ol Molk Mosque located in Shiraz, Iran)

Colors can look diﬀerently depending on their surrounding colors and shapes. The two small squares have exactly the same color, but the right one looks slightly darker.

sumably different color perceptions that cannot readily be compared to one another. The mere presence of “extra” photoreceptor types does not directly imply that they are being used functionally in an animal. Demonstrating improved spectral discrimination in any animal can be difficult since complex sets of neurons affect color perception in ways that are generally difficult to interrogate.[1] 20 CHAPTER 2. DAY 2

The science of color is sometimes called chromatics, colorimetry, or simply color science. It includes the perception of color by the human eye and brain, the origin of color in materials, color theory in art, and the physics of electromagnetic radiation in the visible range (that is, what is commonly referred to simply as light).

2.1.1 Physics of color

Continuous optical spectrum rendered into the sRGB color space.

Electromagnetic radiation is characterized by its wavelength (or frequency) and its intensity. When the wavelength is within the visible spectrum (the range of wavelengths humans can perceive, approximately from 390 nm to 700 nm), it is known as “visible light”. Most light sources emit light at many different wavelengths; a source’s spectrum is a distribution giving its intensity at each wavelength. Although the spectrum of light arriving at the eye from a given direction determines the color sensation in that direction, there are many more possible spectral combinations than color sensations. In fact, one may formally define a color as a class of spectra that give rise to the same color sensation, although such classes would vary widely among different species, and to a lesser extent among individuals within the same species. In each such class the members are called metamers of the color in question.

Spectral colors

The familiar colors of the rainbow in the spectrum – named using the Latin word for appearance or apparition by Isaac Newton in 1671 – include all those colors that can be produced by visible light of a single wavelength only, the pure spectral or monochromatic colors. The table at right shows approximate frequencies (in terahertz) and wavelengths (in nanometers) for various pure spectral colors. The wavelengths listed are as measured in air or vacuum (see refractive index). The color table should not be interpreted as a deﬁnitive list – the pure spectral colors form a continuous spectrum, and how it is divided into distinct colors linguistically is a matter of culture and historical contingency (although people everywhere have been shown to perceive colors in the same way[3]). A common list identiﬁes six main bands: red, orange, yellow, green, blue, and violet. Newton’s conception included a seventh color, indigo, between blue and violet. It is possible that what Newton referred to as blue is nearer to what today is known as cyan, and that indigo was simply the dark blue of the indigo dye that was being imported at the time.[4] The intensity of a spectral color, relative to the context in which it is viewed, may alter its perception considerably; for example, a low-intensity orange-yellow is brown, and a low-intensity yellow-green is olive-green.

Color of objects

The color of an object depends on both the physics of the object in its environment and the characteristics of the perceiving eye and brain. Physically, objects can be said to have the color of the light leaving their surfaces, which normally depends on the spectrum of the incident illumination and the reflectance properties of the surface, as well as potentially on the angles of illumination and viewing. Some objects not only reflect light, but also transmit light or emit light themselves, which also contribute to the color. A viewer’s perception of the object’s color depends not only on the spectrum of the light leaving its surface, but also on a host of contextual cues, so that color differences between objects can be discerned mostly independent of the lighting spectrum, viewing angle, etc. This effect is known as color constancy. Some generalizations of the physics can be drawn, neglecting perceptual effects for now:

• Light arriving at an opaque surface is either reflected "specularly" (that is, in the manner of a mirror), scattered (that is, reflected with diffuse scattering), or absorbed – or some combination of these.

• Opaque objects that do not reﬂect specularly (which tend to have rough surfaces) have their color determined by which wavelengths of light they scatter strongly (with the light that is not scattered being absorbed). If 2.1. COLOR 21

The upper disk and the lower disk have exactly the same objective color, and are in identical gray surroundings; based on context differences, humans perceive the squares as having different reflectances, and may interpret the colors as different color categories; see checker shadow illusion.

objects scatter all wavelengths with roughly equal strength, they appear white. If they absorb all wavelengths, they appear black.

• Opaque objects that specularly reflect light of different wavelengths with different efficiencies look like mirrors tinted with colors determined by those differences. An object that reflects some fraction of impinging light and absorbs the rest may look black but also be faintly reflective; examples are black objects coated with layers of enamel or lacquer.

• Objects that transmit light are either translucent (scattering the transmitted light) or transparent (not scattering the transmitted light). If they also absorb (or reflect) light of various wavelengths differentially, they appear tinted with a color determined by the nature of that absorption (or that reflectance).

• Objects may emit light that they generate from having excited electrons, rather than merely reﬂecting or transmitting light. The electrons may be excited due to elevated temperature (incandescence), as a result of chemical reactions (chemoluminescence), after absorbing light of other frequencies ("ﬂuorescence" or "phosphorescence") or from electrical contacts as in light emitting diodes, or other light sources.

To summarize, the color of an object is a complex result of its surface properties, its transmission properties, and its emission properties, all of which contribute to the mix of wavelengths in the light leaving the surface of the object. The perceived color is then further conditioned by the nature of the ambient illumination, and by the color properties of other objects nearby, and via other characteristics of the perceiving eye and brain. 22 CHAPTER 2. DAY 2

When viewed in full size, this image contains about 16 million pixels, each corresponding to a diﬀerent color on the full set of RGB colors. The human eye can distinguish about 10 million diﬀerent colors.[5]

2.1.2 Perception

Development of theories of color vision

Main article: Color theory

Although Aristotle and other ancient scientists had already written on the nature of light and color vision, it was not until Newton that light was identified as the source of the color sensation. In 1810, Goethe published his comprehensive Theory of Colors in which he ascribed physiological effects to color that are now understood as psychological. In 1801 Thomas Young proposed his trichromatic theory, based on the observation that any color could be matched with a combination of three lights. This theory was later refined by James Clerk Maxwell and Hermann von Helmholtz. As Helmholtz puts it, “the principles of Newton’s law of mixture were experimentally confirmed by Maxwell in 1856. Young’s theory of color sensations, like so much else that this marvelous investigator achieved in advance of his time, remained unnoticed until Maxwell directed attention to it.”[6] At the same time as Helmholtz, Ewald Hering developed the opponent process theory of color, noting that color blindness and afterimages typically come in opponent pairs (red-green, blue-orange, yellow-violet, and black-white). 2.1. COLOR 23

Ultimately these two theories were synthesized in 1957 by Hurvich and Jameson, who showed that retinal processing corresponds to the trichromatic theory, while processing at the level of the lateral geniculate nucleus corresponds to the opponent theory.[7] In 1931, an international group of experts known as the Commission internationale de l'éclairage (CIE) developed a mathematical color model, which mapped out the space of observable colors and assigned a set of three numbers to each.

Color in the eye

Main article: Color vision The ability of the human eye to distinguish colors is based upon the varying sensitivity of diﬀerent cells in the retina

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0.2

0 400 450 500 550 600 650 700

Normalized typical human cone cell responses (S, M, and L types) to monochromatic spectral stimuli to light of different wavelengths. Humans being trichromatic, the retina contains three types of color receptor cells, or cones. One type, relatively distinct from the other two, is most responsive to light that is perceived as blue or blue- violet, with wavelengths around 450 nm; cones of this type are sometimes called short-wavelength cones, S cones, or blue cones. The other two types are closely related genetically and chemically: middle-wavelength cones, M cones, or green cones are most sensitive to light perceived as green, with wavelengths around 540 nm, while the long-wavelength cones, L cones, or red cones, are most sensitive to light is perceived as greenish yellow, with wavelengths around 570 nm. Light, no matter how complex its composition of wavelengths, is reduced to three color components by the eye. For each location in the visual field, the three types of cones yield three signals based on the extent to which each is stimulated. These amounts of stimulation are sometimes called tristimulus values. The response curve as a function of wavelength varies for each type of cone. Because the curves overlap, some tristimulus values do not occur for any incoming light combination. For example, it is not possible to stimulate only the mid-wavelength (so-called “green”) cones; the other cones will inevitably be stimulated to some degree at the same time. The set of all possible tristimulus values determines the human color space. It has been estimated that humans can distinguish roughly 10 million different colors.[5] 24 CHAPTER 2. DAY 2

The other type of light-sensitive cell in the eye, the rod, has a diﬀerent response curve. In normal situations, when light is bright enough to strongly stimulate the cones, rods play virtually no role in vision at all.[8] On the other hand, in dim light, the cones are understimulated leaving only the signal from the rods, resulting in a colorless response. (Furthermore, the rods are barely sensitive to light in the “red” range.) In certain conditions of intermediate illumination, the rod response and a weak cone response can together result in color discriminations not accounted for by cone responses alone. These eﬀects, combined, are summarized also in the Kruithof curve, that describes the change of color perception and pleasingness of light as function of temperature and intensity.

Color in the brain

Main article: Color vision While the mechanisms of color vision at the level of the retina are well-described in terms of tristimulus values, color

The visual dorsal stream (green) and ventral stream (purple) are shown. The ventral stream is responsible for color perception.

processing after that point is organized diﬀerently. A dominant theory of color vision proposes that color information is transmitted out of the eye by three opponent processes, or opponent channels, each constructed from the raw output of the cones: a red–green channel, a blue–yellow channel, and a black–white “luminance” channel. This theory has been supported by neurobiology, and accounts for the structure of our subjective color experience. Speciﬁcally, it explains why humans cannot perceive a “reddish green” or “yellowish blue”, and it predicts the color wheel: it is the collection of colors for which at least one of the two color channels measures a value at one of its extremes. The exact nature of color perception beyond the processing already described, and indeed the status of color as a feature of the perceived world or rather as a feature of our perception of the world – a type of qualia – is a matter of complex and continuing philosophical dispute.

Nonstandard color perception

Color deﬁciency Main article: Color blindness 2.1. COLOR 25

If one or more types of a person’s color-sensing cones are missing or less responsive than normal to incoming light, that person can distinguish fewer colors and is said to be color deficient or color blind (though this latter term can be misleading; almost all color deficient individuals can distinguish at least some colors). Some kinds of color deficiency are caused by anomalies in the number or nature of cones in the retina. Others (like central or cortical achromatopsia) are caused by neural anomalies in those parts of the brain where visual processing takes place.

Tetrachromacy Main article: Tetrachromacy

While most humans are trichromatic (having three types of color receptors), many animals, known as tetrachromats, have four types. These include some species of spiders, most marsupials, birds, reptiles, and many species of fish. Other species are sensitive to only two axes of color or do not perceive color at all; these are called dichromats and monochromats respectively. A distinction is made between retinal tetrachromacy (having four pigments in cone cells in the retina, compared to three in trichromats) and functional tetrachromacy (having the ability to make enhanced color discriminations based on that retinal difference). As many as half of all women are retinal tetrachromats.[9]:p.256 The phenomenon arises when an individual receives two slightly different copies of the gene for either the medium- or long-wavelength cones, which are carried on the x-chromosome. To have two different genes, a person must have two x-chromosomes, which is why the phenomenon only occurs in women.[9] There is one scholarly report that confirms the existence of a functional tetrachromat.[10]

Synesthesia In certain forms of synesthesia/ideasthesia, perceiving letters and numbers (grapheme–color synesthesia) or hearing musical sounds (music–color synesthesia) will lead to the unusual additional experiences of seeing colors. Behavioral and functional neuroimaging experiments have demonstrated that these color experiences lead to changes in behavioral tasks and lead to increased activation of brain regions involved in color perception, thus demonstrating their reality, and similarity to real color percepts, albeit evoked through a non-standard route.

Afterimages

After exposure to strong light in their sensitivity range, photoreceptors of a given type become desensitized. For a few seconds after the light ceases, they will continue to signal less strongly than they otherwise would. Colors observed during that period will appear to lack the color component detected by the desensitized photoreceptors. This effect is responsible for the phenomenon of afterimages, in which the eye may continue to see a bright figure after looking away from it, but in a complementary color. Afterimage effects have also been utilized by artists, including Vincent van Gogh.

Color constancy

Main article: Color constancy

When an artist uses a limited color palette, the eye tends to compensate by seeing any gray or neutral color as the color which is missing from the color wheel. For example, in a limited palette consisting of red, yellow, black, and white, a mixture of yellow and black will appear as a variety of green, a mixture of red and black will appear as a variety of purple, and pure gray will appear bluish.[11] The trichromatic theory is strictly true when the visual system is in a fixed state of adaptation. In reality, the visual system is constantly adapting to changes in the environment and compares the various colors in a scene to reduce the effects of the illumination. If a scene is illuminated with one light, and then with another, as long as the difference between the light sources stays within a reasonable range, the colors in the scene appear relatively constant to us. This was studied by Edwin Land in the 1970s and led to his retinex theory of color constancy. It should be noted, that both phenomena are readily explained and mathematically modeled with modern theories of chromatic adaptation and color appearance (e.g. CIECAM02, iCAM).[12] There is no need to dismiss the trichromatic theory of vision, but rather it can be enhanced with an understanding of how the visual system adapts to changes in the viewing environment. 26 CHAPTER 2. DAY 2

Color naming

Main article: Color term See also: Lists of colors and Web colors

Colors vary in several diﬀerent ways, including hue (shades of red, orange, yellow, green, blue, and violet), saturation, brightness, and gloss. Some color words are derived from the name of an object of that color, such as "orange" or "salmon", while others are abstract, like “red”. In the 1969 study Basic Color Terms: Their Universality and Evolution, Brent Berlin and Paul Kay describe a pattern in naming “basic” colors (like “red” but not “red-orange” or “dark red” or “blood red”, which are “shades” of red). All languages that have two “basic” color names distinguish dark/cool colors from bright/warm colors. The next colors to be distinguished are usually red and then yellow or green. All languages with six “basic” colors include black, white, red, green, blue, and yellow. The pattern holds up to a set of twelve: black, gray, white, pink, red, orange, yellow, green, blue, purple, brown, and azure (distinct from blue in Russian and Italian, but not English).

2.1.3 Associations

Individual colors have a variety of cultural associations such as national colors (in general described in individual color articles and color symbolism). The field of color psychology attempts to identify the effects of color on human emotion and activity. Chromotherapy is a form of alternative medicine attributed to various Eastern traditions. Colors have different associations in different countries and cultures.[13] Different colors have been demonstrated to have effects on cognition. For example, researchers at the University of Linz in Austria demonstrated that the color red significantly decreases cognitive functioning in men.[14]

2.1.4 Spectral colors and color reproduction

Most light sources are mixtures of various wavelengths of light. Many such sources can still effectively produce a spectral color, as the eye cannot distinguish them from single-wavelength sources. For example, most computer displays reproduce the spectral color orange as a combination of red and green light; it appears orange because the red and green are mixed in the right proportions to allow the eye’s cones to respond the way they do to the spectral color orange. A useful concept in understanding the perceived color of a non-monochromatic light source is the dominant wavelength, which identifies the single wavelength of light that produces a sensation most similar to the light source. Dominant wavelength is roughly akin to hue. There are many color perceptions that by definition cannot be pure spectral colors due to desaturation or because they are purples (mixtures of red and violet light, from opposite ends of the spectrum). Some examples of necessarily non-spectral colors are the achromatic colors (black, gray, and white) and colors such as pink, tan, and magenta. Two different light spectra that have the same effect on the three color receptors in the human eye will be perceived as the same color. They are metamers of that color. This is exemplified by the white light emitted by fluorescent lamps, which typically has a spectrum of a few narrow bands, while daylight has a continuous spectrum. The human eye cannot tell the difference between such light spectra just by looking into the light source, although reflected colors from objects can look different. (This is often exploited; for example, to make fruit or tomatoes look more intensely red.) Similarly, most human color perceptions can be generated by a mixture of three colors called primaries. This is used to reproduce color scenes in photography, printing, television, and other media. There are a number of methods or color spaces for specifying a color in terms of three particular primary colors. Each method has its advantages and disadvantages depending on the particular application. No mixture of colors, however, can produce a response truly identical to that of a spectral color, although one can get close, especially for the longer wavelengths, where the CIE 1931 color space chromaticity diagram has a nearly straight edge. For example, mixing green light (530 nm) and blue light (460 nm) produces cyan light that is slightly desaturated, because response of the red color receptor would be greater to the green and blue light in the mixture than it would be to a pure cyan light at 485 nm that has the same intensity as the mixture of blue and green. Because of this, and because the primaries in color printing systems generally are not pure themselves, the colors 2.1. COLOR 27

0.9 520

0.8 540

0.7 560 0.6 500 0.5 580 y 0.4 600

620 0.3 490 700

0.2

480 0.1 470 460 0.0 380 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 x

The CIE 1931 color space chromaticity diagram. The outer curved boundary is the spectral (or monochromatic) locus, with wavelengths shown in nanometers. The colors depicted depend on the color space of the device on which you are viewing the image, and therefore may not be a strictly accurate representation of the color at a particular position, and especially not for monochromatic colors.

reproduced are never perfectly saturated spectral colors, and so spectral colors cannot be matched exactly. However, natural scenes rarely contain fully saturated colors, thus such scenes can usually be approximated well by these systems. The range of colors that can be reproduced with a given color reproduction system is called the gamut. The CIE chromaticity diagram can be used to describe the gamut. Another problem with color reproduction systems is connected with the acquisition devices, like cameras or scanners. The characteristics of the color sensors in the devices are often very far from the characteristics of the receptors in the human eye. In effect, acquisition of colors can be relatively poor if they have special, often very “jagged”, spectra caused for example by unusual lighting of the photographed scene. A color reproduction system “tuned” to a human with normal color vision may give very inaccurate results for other observers. The different color response of different devices can be problematic if not properly managed. For color information 28 CHAPTER 2. DAY 2 stored and transferred in digital form, color management techniques, such as those based on ICC profiles, can help to avoid distortions of the reproduced colors. Color management does not circumvent the gamut limitations of particular output devices, but can assist in finding good mapping of input colors into the gamut that can be reproduced.

2.1.5 Additive coloring

Additive color mixing: combining red and green yields yellow; combining all three primary colors together yields white.

Additive color is light created by mixing together light of two or more diﬀerent colors. Red, green, and blue are the additive primary colors normally used in additive color systems such as projectors and computer terminals.

2.1.6 Subtractive coloring

Subtractive coloring uses dyes, inks, pigments, or filters to absorb some wavelengths of light and not others. The color that a surface displays comes from the parts of the visible spectrum that are not absorbed and therefore remain visible. Without pigments or dye, fabric fibers, paint base and paper are usually made of particles that scatter white light (all colors) well in all directions. When a pigment or ink is added, wavelengths are absorbed or “subtracted” from white light, so light of another color reaches the eye. If the light is not a pure white source (the case of nearly all forms of artificial lighting), the resulting spectrum will 2.1. COLOR 29

Subtractive color mixing: combining yellow and magenta yields red; combining all three primary colors together yields black appear a slightly diﬀerent color. Red paint, viewed under blue light, may appear black. Red paint is red because it scatters only the red components of the spectrum. If red paint is illuminated by blue light, it will be absorbed by the red paint, creating the appearance of a black object.

2.1.7 Structural color

Further information: Structural coloration and Animal coloration

Structural colors are colors caused by interference effects rather than by pigments. Color effects are produced when a material is scored with fine parallel lines, formed of one or more parallel thin layers, or otherwise composed of microstructures on the scale of the color’s wavelength. If the microstructures are spaced randomly, light of shorter wavelengths will be scattered preferentially to produce Tyndall effect colors: the blue of the sky (Rayleigh scattering, caused by structures much smaller than the wavelength of light, in this case air molecules), the luster of opals, and the blue of human irises. If the microstructures are aligned in arrays, for example the array of pits in a CD, they behave as a diffraction grating: the grating reflects different wavelengths in different directions due to interference phenomena, separating mixed “white” light into light of different wavelengths. If the structure is one or more thin layers then it will reflect some wavelengths and transmit others, depending on the layers’ thickness. 30 CHAPTER 2. DAY 2

Structural color is studied in the field of thin-film optics. A layman’s term that describes particularly the most ordered or the most changeable structural colors is iridescence. Structural color is responsible for the blues and greens of the feathers of many birds (the blue jay, for example), as well as certain butterfly wings and beetle shells. Variations in the pattern’s spacing often give rise to an iridescent effect, as seen in peacock feathers, soap bubbles, films of oil, and mother of pearl, because the reflected color depends upon the viewing angle. Numerous scientists have carried out research in butterfly wings and beetle shells, including Isaac Newton and Robert Hooke. Since 1942, electron micrography has been used, advancing the development of products that exploit structural color, such as "photonic" cosmetics.[15]

2.1.8 Mentions of color in social media

According to Pantone, the top three colors in social media for 2012 were red (186 million mentions; accredited to Taylor Swift's Red album, NASA's landing on Mars, and red carpet coverage), blue (125 million mentions; accredited to the United States presidential election, 2012, Mars rover Curiosity ﬁnding blue rocks, and blue sports teams), and Green (102 million mentions; accredited to “environmental friendliness”, Green Bay Packers, and green eyed girls).[16]

2.1.9 Additional terms

• Color wheel: an illustrative organization of color hues in a circle that shows relationships.

• Colorfulness, chroma, purity, or saturation: how “intense” or “concentrated” a color is. Technical deﬁnitions distinguish between colorfulness, chroma, and saturation as distinct perceptual attributes and include purity as a physical quantity. These terms, and others related to light and color are internationally agreed upon and published in the CIE Lighting Vocabulary.[17] More readily available texts on colorimetry also deﬁne and explain these terms.[12][18]

• Dichromatism: a phenomenon where the hue is dependent on concentration and/or thickness of the absorbing substance.

• Hue: the color’s direction from white, for example in a color wheel or chromaticity diagram.

• Shade: a color made darker by adding black.

• Tint: a color made lighter by adding white.

• Value, brightness, lightness, or luminosity: how light or dark a color is.

2.1.10 See also

• Chromophore

• Color analysis (art)

• Color mapping

• Complementary color

• Impossible color

• International Color Consortium

• International Commission on Illumination

• Lists of colors (compact version)

• Neutral color

• Pearlescent coating including Metal eﬀect pigments

• Primary, secondary and tertiary colors 2.1. COLOR 31

2.1.11 References

[1] Morrison, Jessica (23 January 2014). “Mantis shrimp’s super colour vision debunked”. Nature. doi:10.1038/nature.2014.14578. [2] Craig F. Bohren (2006). Fundamentals of Atmospheric Radiation: An Introduction with 400 Problems. Wiley-VCH. ISBN 3-527-40503-8. [3] Berlin, B. and Kay, P., Basic Color Terms: Their Universality and Evolution, Berkeley: University of California Press, 1969. [4] Waldman, Gary (2002). Introduction to light : the physics of light, vision, and color (Dover ed.). Mineola: Dover Publica- tions. p. 193. ISBN 978-0-486-42118-6. [5] Judd, Deane B.; Wyszecki, Günter (1975). Color in Business, Science and Industry. Wiley Series in Pure and Applied Optics (third ed.). New York: Wiley-Interscience. p. 388. ISBN 0-471-45212-2. [6] Hermann von Helmholtz, Physiological Optics – The Sensations of Vision, 1866, as translated in Sources of Color Science, David L. MacAdam, ed., Cambridge: MIT Press, 1970. [7] Palmer, S.E. (1999). Vision Science: Photons to Phenomenology, Cambridge, MA: MIT Press. ISBN 0-262-16183-4. [8] “Under well-lit viewing conditions (photopic vision), cones ...are highly active and rods are inactive.” Hirakawa, K.; Parks, T.W. (2005). Chromatic Adaptation and White-Balance Problem (PDF). IEEE ICIP. doi:10.1109/ICIP.2005.1530559. Archived from the original (PDF) on November 28, 2006. [9] Jameson, K. A.; Highnote, S. M.,; Wasserman, L. M. (2001). “Richer color experience in observers with multiple pho- topigment opsin genes.” (PDF). Psychonomic Bulletin and Review. 8 (2): 244–261. doi:10.3758/BF03196159. PMID 11495112. [10] Jordan, G.; Deeb, S. S.; Bosten, J. M.; Mollon, J. D. (20 July 2010). “The dimensionality of color vision in carriers of anomalous trichromacy”. Journal of Vision. 10 (8): 12–12. doi:10.1167/10.8.12. PMID 20884587. [11] Depauw, Robert C. “United States Patent”. Retrieved 20 March 2011. [12] M.D. Fairchild, Color Appearance Models Archived May 5, 2011, at the Wayback Machine., 2nd Ed., Wiley, Chichester (2005). [13] “Chart: Color Meanings by Culture”. Retrieved 2010-06-29. [14] Gnambs, Timo; Appel, Markus; Batinic, Bernad (2010). “Color red in web-based knowledge testing”. Computers in Human Behavior. 26: 1625–1631. doi:10.1016/j.chb.2010.06.010. [15] “Economic and Social Research Council – Science in the Dock, Art in the Stocks”. Archived from the original on November 2, 2007. Retrieved 2007-10-07. [16] “Celebrate Color”. pantone.com. Pantone. Retrieved 7 December 2014. [17] CIE Pub. 17-4, International Lighting Vocabulary, 1987. http://www.cie.co.at/publ/abst/17-4-89.html [18] R.S. Berns, Principles of Color Technology, 3rd Ed., Wiley, New York (2001).

2.1.12 External links and sources

• Bibliography Database on Color Theory, Buenos Aires University • Maund, Barry. “Color”. Stanford Encyclopedia of Philosophy. • “Color”. Internet Encyclopedia of Philosophy. • Why Should Engineers and Scientists Be Worried About Color? • Robert Ridgway's A Nomenclature of Colors (1886) and Color Standards and Color Nomenclature (1912) – text-searchable digital facsimiles at Linda Hall Library • Albert Henry Munsell's A Color Notation, (1907) at Project Gutenberg • AIC, International Colour Association • The Eﬀect of Color | OFF BOOK Documentary produced by Oﬀ Book (web series) • Study of the history of colors • The Color of Consciousness Chapter 3

Day 3

3.1 Color wheel

For other uses, see Color wheel (disambiguation). A color wheel or colour circle[1] is an abstract illustrative organization of color hues around a circle, which shows

Boutet’s 7-color and 12-color color circles from 1708 the relationships between primary colors, secondary colors, tertiary colors etc. Some sources use the terms color wheel and color circle interchangeably;[2][3] however, one term or the other may be more prevalent in certain ﬁelds or certain versions as mentioned above. For instance, some reserve the term color wheel for mechanical rotating devices, such as color tops or ﬁlter wheels. Others classify various color wheels as color disc, color chart, and color scale varieties.[4]

32 3.1. COLOR WHEEL 33

As an illustrative model, artists typically use red, yellow, and blue primaries (RYB color model) arranged at three equally spaced points around their color wheel.[5] Printers and others who use modern subtractive color methods and terminology use magenta, yellow, and cyan as subtractive primaries. Intermediate and interior points of color wheels and circles represent color mixtures. In a paint or subtractive color wheel, the “center of gravity” is usually (but not always[6]) black, representing all colors of light being absorbed; in a color circle, on the other hand, the center is white or gray, indicating a mixture of diﬀerent wavelengths of light (all wavelengths, or two complementary colors, for example). The arrangement of colors around the color circle is often considered to be in correspondence with the wavelengths of light, as opposed to hues, in accord with the original color circle of Isaac Newton. Modern color circles include the purples, however, between red and violet.[7] Color scientists and psychologists often use the additive primaries, red, green and blue; and often refer to their arrangement around a circle as a color circle as opposed to a color wheel.[8]

3.1.1 Colors of the color wheel

The typical artists’ paint or pigment color wheel includes the blue, red, and yellow primary colors. The corresponding secondary colors are green, orange, and violet or purple. The tertiary colors are green-yellow, yellow–orange, orange- red, red–violet, violet-blue and blue–green. A color wheel based on RGB (red, green, blue) or RGV (red, green, violet) additive primaries has cyan, magenta, and yellow secondaries (cyan was previously known as cyan blue). Alternatively, the same arrangement of colors around a circle can be described as based on cyan, magenta, and yellow subtractive primaries, with red, green, and blue (or violet) being secondaries. Most color wheels are based on three primary colors, three secondary colors, and the six intermediates formed by mixing a primary with a secondary, known as tertiary colors, for a total of 12 main divisions; some add more intermediates, for 24 named colors. Other color wheels, however, are based on the four opponent colors, and may have four or eight main colors. Goethe's Theory of Colours provided the first systematic study of the physiological effects of color (1810). His observations on the effect of opposed colors led him to a symmetric arrangement of his color wheel anticipating Ewald Hering's opponent color theory (1872).

...for the colours diametrically opposed to each other... are those that reciprocally evoke each other in the eye. — Goethe, Theory of Colours

3.1.2 The color circle and color vision

A color circle based on spectral wavelengths appears with red at one end of the spectrum and violet at the other. A wedge-shaped gap represents colors that have no unique spectral frequency. These extra-spectral colors, the purples, form from additive mixture of colors from the ends of the spectrum. In normal human vision, wavelengths of between about 400 nm and 700 nm are represented by this incomplete circle, with the longer wavelengths equating to the red end of the spectrum. Complement colors are located directly opposite each other on this wheel. These complement colors are not identical to colors in pigment mixing (such as are used in paint), but when lights are additively mixed in the correct proportions appear as a neutral grey or white.[9] For example: the reason that the Wimbledon tennis tournament uses purple on the Wimbledon oﬃcial logo is that purple is located almost opposite of green on the color wheel. Purple against green provides good contrast.[10] The color circle is used for, among other purposes, illustrating additive color mixture. Combining two colored lights from diﬀerent parts of the spectrum may produce a third color that appears like a light from another part of the spectrum, even though dissimilar wavelengths are involved. This type of color matching is known as metameric matching.[11] Thus a combination of green and red light might produce a color close to yellow in apparent hue. The newly formed color lies between the two original colors on the color circle, but they are usually represented as being joined by a straight line on the circle, the location of the new color closer to the (white) centre of the circle indicating that the resulting hue is less saturated (i.e., paler) than either of the two source colors. The combination of any two colors in this way are always less saturated than the two pure spectral colors individually. 34 CHAPTER 3. DAY 3

Objects may be viewed under a variety of different lighting conditions. The human visual system is able to adapt to these differences by chromatic adaptation. This aspect of the visual system is relatively easy to mislead, and optical illusions relating to color are therefore a common phenomenon. The color circle is a useful tool for examining these illusions. Arranging spectral colors in a circle to predict admixture of light stems from work by Sir Isaac Newton. Newton’s calculation of the resulting color involves three steps: First, mark on the color circle the constituent colors according to their relative weight. Second, find the barycenter of these differently weighted colors. Third, interpret the radial distance (from the center of the circle to the barycenter) as the saturation of the color, and the azimuthal position on the circle as the hue of the color. Thus, Newton’s color circle is a predecessor of the modern, horseshoe-shaped CIE color diagram. The psychophysical theory behind the color circle dates to the early color triangle of Thomas Young, whose work was later extended by James Clerk Maxwell and Hermann von Helmholtz. Young postulated that the eye contains receptors that respond to three different primary sensations, or spectra of light. As Maxwell showed, all hues, but not all colors, can be created from three primary colors such as red, green, and blue, if they are mixed in the right proportions.

3.1.3 Color wheels and paint color mixing

There is no straight-line relationship between colors mixed in pigment, which vary from medium to medium. With a psychophysical color circle, however, the resulting hue of any mixture of two colored light sources can be determined simply by the relative brightness and wavelength of the two lights.[11] A similar calculation cannot be performed with two paints. As such, a painter’s color wheel is indicative rather than predictive, being used to compare existing colors rather than calculate exact colors of mixtures. Because of diﬀerences relating to the medium, diﬀerent color wheels can be created according to the type of paint or other medium used, and many artists make their own individual color wheels. These often contain only blocks of color rather than the gradation between tones that is characteristic of the color circle.[12]

3.1.4 Color wheel software

Main article: Color tool

A number of interactive color wheel applications are available both on the Internet and as desktop applications. These programs are used by artists and designers for picking colors for a design.

3.1.5 HSV color wheel

The HSL and HSV color spaces are simple geometric transformations of the RGB cube into cylindrical form. The outer top circle of the HSV cylinder – or the outer middle circle of the HSL cylinder – can be thought of as a color wheel. There is no authoritative way of labeling the colors in such a color wheel, but the six colors which fall at corners of the RGB cube are given names in the X11 color list, and are named keywords in HTML.[13]

3.1.6 Color schemes

Main article: Color scheme

Color schemes are logical combinations of colors on the color wheel. In color theory, a color scheme is the choice of colors used in design for a range of media. For example, the use of a white background with black text is an example of a common default color scheme in web design. Color schemes are used to create style and appeal. Colors that create an aesthetic feeling together commonly appear together in color schemes. A basic color scheme uses two colors that look appealing together. More advanced color schemes involve several colors in combination, usually based around a single color—for example, text with such colors as red, yellow, orange and light blue arranged together on a black background in a magazine article. 3.1. COLOR WHEEL 35

Color schemes can also contain diﬀerent shades of a single color; for example, a color scheme that mixes diﬀerent shades of green, ranging from very light (almost white) to very dark. For a list of ways to construct color schemes, regarding properties such as warmness/achromiticness/complementariness, see color theory.

3.1.7 Gallery

3.1.8 See also

• Color theory

• Visual perception

• Psychophysics

• Color solid

• Spectral color

• Octave

• Color blind

• Ishihara test

3.1.9 References

[1] Morton, J.L. “Basic Color Theory”. Color Matters.

[2] Simon Jennings (2003). Artist’s Color Manual: The Complete Guide to Working With Color. Chronicle Books. ISBN 0-8118-4143-X.

[3] Faber Birren (1934). Color Dimensions: Creating New Principles of Color Harmony and a Practical Equation in Color Deﬁnition. Chicago: The Crimson Press. ISBN 1-4286-5179-9.

[4] Joseph Anthony Gillet and William James Rolfe (1881). Elements of Natural Philosophy: For the Use of Schools and Academies. New York: Potter, Ainsworth.

[5] Kathleen Lochen Staiger (2006). The Oil Painting Course You've Always Wanted: Guided Lessons for Beginners. Watson– Guptill. ISBN 0-8230-3259-0.

[6] Martha Gill (2000). Color Harmony Pastels: A Guidebook for Creating Great Color Combinations. Rockport Publishers. ISBN 1-56496-720-4.

[7] Steven K. Shevell (2003). The Science of Color. Elsevier. ISBN 0-444-51251-9.

[8] Linda Leal (1994). The Essentials of Psychology. Research & Education Assoc. ISBN 0-87891-930-9.

[9] Krech, D., Crutchﬁeld, R.S., Livson, N., Wilson, W.A. jr., Parducci, A. (1982) Elements of psychology (4th ed.). New York: Alfred A. Knopf. pp. 108-109.

[10] “Natural Court Colors Give Way to a Kaleidoscope of Shades”.

[11] Schiﬀman, H.R. (1990) Sensation and perception: An integrated approach (3rd ed.). New York: John Wiley & Sons, pp. 252-253.

[12] Rodwell, J. (1987) The complete watercolour artist. London: Paul Press, pp. 94-95.

[13] “Basic HTML data types”. HTML 4.01 Speciﬁcation. W3C. 24 December 1999. 36 CHAPTER 3. DAY 3

3.1.10 External links

• David Briggs (2007). Hue in The Dimensions of Colour • Interactive Color Wheel (Color Scheme Generator)

• “Colour Wheels, Charts, and Tables Through History”. The Public Domain Review. Illustrated history, with links to mostly public domain images from digitized historic books. 3.1. COLOR WHEEL 37

Wilhelm von Bezold’s 1874 Farbentafel 38 CHAPTER 3. DAY 3

A 1908 color wheel with red, green, and violet “plus colors” and magenta, yellow, and cyan blue “minus colors” 3.1. COLOR WHEEL 39

A 1917 four-way color circle related to the color opponent process 40 CHAPTER 3. DAY 3

A color wheel based on HSV, labeled with HTML color keywords Chapter 4

Day 4

4.1 Spectral color

A spectral color is a color that is evoked by a single wavelength of light in the visible spectrum, or by a relatively narrow band of wavelengths, also known as monochromatic light. Every wavelength of visible light is perceived as a spectral color, in a continuous spectrum; the colors of suﬃciently close wavelengths are indistinguishable. The spectrum is often divided into named colors, though any division is somewhat arbitrary: the spectrum is continuous. Traditional colors include: red, orange, yellow, green, blue, and violet. The division used by Isaac Newton, in his color wheel, was: red, orange, yellow, green, blue, indigo and violet; a mnemonic for this order is "Roy G. Biv". In modern divisions of the spectrum, indigo is often omitted. One needs at least trichromatic color vision for there to be a distinction between spectral and non-spectral colours : trichromacy gives a possibility to perceive both hue and saturation in the chroma. In color models capable to represent spectral colors,[1] such as CIELUV, a spectral color has the maximal saturation

4.1.1 In color spaces

In color spaces which include all, or most spectral colors, they form a part of boundary of the set of all real colors. If luminance is counted, then spectral colors form a surface, otherwise their locus is a curve in a two-dimensional chromaticity space. Theoretically, only RGB-implemented colors which might be really spectral are its primaries: red, green, and blue, whereas any other (mixed) color is inherently non-spectral. But due to different chromaticity properties of different spectral segments, and also due to practical limitations of light sources, the actual distance between RGB pure color wheel colors and spectral colors shows a complicated dependence on the hue. Due to location of R and G primaries near the almost “flat” spectral segment, RGB color space is reasonably good with approximating spectral orange, yellow, and bright (yellowish) green, but is especially poor in reaching a visual appearance of spectral colors between green and blue, as well as extreme spectral colors. The sRGB standard has an additional problem with its “red” primary which is shifted to orange due to a trade-off between purity of red and its reasonable luminance, so that the red spectral became unreachable. Some samples in the table below provide only rough approximations of spectral and near-spectral colors. CMYK is usually even poorer than RGB in its reach of spectral colors, with notable exception of process yellow, which is rather close to spectral colors due to aforementioned flatness of the spectral locus in the red–green segment. Note that spectral color are universally included to scientific color models such as CIE 1931, but industrial and consumer color spaces such as sRGB, CMYK, and Pantone, do not include any of spectral colors.

4.1.2 Table of spectral or near-spectral colors

Most of the colors listed do not reach the maximal (spectral) colorfulness, or are not usually seen with it, but they can be saturated enough to be perceived closely to their dominant wavelength spectral colors. Ranges of wavelengths

41 42 CHAPTER 4. DAY 4

0.9 520

0.8 540

0.7 560 0.6 500 0.5 580 y 0.4 600 620 0.3

0.2

480 0.1

0.0 460 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 x

The CIE xy chromaticity diagram. The spectrum colors are the colors on the horseshoe-shaped curve on the outside of the diagram. All other colors are not spectral: the bottom straight line is the line of purples, whilst within the interior of the diagram are unsaturated colors that are various mixtures of a spectral color or a purple color with white, a grayscale color. White is in the central part of the interior of the diagram, since when all colors of light are mixed together, they produce white. and frequencies are only approximate. Wavelengths and frequencies in gray indicate dominant wavelengths and frequencies, not actual range of spectrum composing a speciﬁed color, which extends farther to both sides and is averaged by receptors to give a near-spectral appearance.

4.1.3 Non-spectral colors

Among some of the colors that are not spectral colors are:

• Grayscale (achromatic) colors, such as white, gray, and black. • Any color obtained by mixing a gray-scale color and another color (either spectral or not), such as pink (a mixture of a reddish color and white) or brown (a mixture of orange and black or gray). 4.1. SPECTRAL COLOR 43

This metrically accurate diagram shows that the spectral locus is almost ﬂat on the red – bright green segment, is strongly curved around green, and becomes less curved between green/cyan and blue

• Violet-red colors, which in color theory include line of purples colors (such as, approximately, magenta and rose), and other variations of purple and red.

• Impossible colors, which can not be seen under normal viewing of light, such as over-saturated colors or colors that are seemingly brighter than white.

4.1.4 See also

• Imaginary color

4.1.5 References

[1] HSL and HSV do not qualify because many spectral colors lie rather far from its gamut.

[2] Samples (allegedly in sRGB) currently rely on Wikipedia data which sometimes use poor, unprofessional sources, misin- terpretation of sources, or occasionally contain original researches. 44 CHAPTER 4. DAY 4

[3] Values for the hue (HSL and HSV or an extrapolation, where necessary) currently rely on Wikipedia data which are prone to miscalculation and other irregularities. Also note that RGB is not an absolute color space, and certain speciﬁc standard (such as sRGB) is necessary to map RGB hues to near-spectral colors.

[4] Thomas J. Bruno, Paris D. N. Svoronos. CRC Handbook of Fundamental Spectroscopic Correlation Charts. CRC Press, 2005. http://hyperphysics.phy-astr.gsu.edu/hbase/vision/specol.html#c1

[5] A proprietary color space

[6] Bisulca, Christina (2008). “UV-Vis-NIR reﬂectance spectroscopy of red lakes in paintings” (PDF). 9th International Con- ference on NDT of Art. ndt.net. Retrieved 2013-06-19.

[7] http://www.cis.rit.edu/research/mcsl2/online/munsell_data/all.dat and commons:File:CIE1931xy blank.svg

[8] Linearly interpolated between two tabulated values.

[9]

[10] Different definitions of RGB give significantly different wavelengths for blue primary, but this does not change the chromaticity greatly.

4.1.6 External links

4.2 Color space

A color space is a specific organization of colors. In combination with physical device profiling, it allows for re- producible representations of color, in both analog and digital representations. A color space may be arbitrary, with particular colors assigned to a set of physical color swatches and corresponding assigned names or numbers such as with the Pantone collection, or structured mathematically, as with NCS System, Adobe RGB or sRGB.A color model is an abstract mathematical model describing the way colors can be represented as tuples of numbers (e.g. triples in RGB or quadruples in CMYK); however, a color model with no associated mapping function to an absolute color space is a more or less arbitrary color system with no connection to any globally understood system of color interpretation. Adding a specific mapping function between a color model and a reference color space establishes within the reference color space a definite “footprint”, known as a gamut, and for a given color model this defines a color space. For example, Adobe RGB and sRGB are two different absolute color spaces, both based on the RGB color model. When defining a color space, the usual reference standard is the CIELAB or CIEXYZ color spaces, which were specifically designed to encompass all colors the average human can see. Since “color space” is a more specific term, identifying a particular combination of color model and mapping function, it tends to be used informally to identify a color model, since identifying a color space automatically identifies the associated color model, however this usage is strictly incorrect. For example, although several specific color spaces are based on the RGB color model, there is no such thing as the singular RGB color space.

4.2.1 Examples

Colors can be created in printing with color spaces based on the CMYK color model, using the subtractive primary colors of pigment (cyan (C), magenta (M), yellow (Y), and black (K)). To create a three-dimensional representation of a given color space, we can assign the amount of magenta color to the representation’s X axis, the amount of cyan to its Y axis, and the amount of yellow to its Z axis. The resulting 3-D space provides a unique position for every possible color that can be created by combining those three pigments. Colors can be created on computer monitors with color spaces based on the RGB color model, using the additive primary colors (red, green, and blue). A three-dimensional representation would assign each of the three colors to the X, Y, and Z axes. Note that colors generated on given monitor will be limited by the reproduction medium, such as the phosphor (in a CRT monitor) or ﬁlters and backlight (LCD monitor). Another way of creating colors on a monitor is with an HSL or HSV color space, based on hue, saturation, brightness (value/brightness). With such a space, the variables are assigned to cylindrical coordinates. Many color spaces can be represented as three-dimensional values in this manner, but some have more, or fewer dimensions, and some, such as Pantone, cannot be represented in this way at all. 4.2. COLOR SPACE 45

0.9 520 ProPhoto RGB

0.8 540 Adobe RGB 1998 0.7 560 Colormatch RGB 0.6 sRGB SWOP CMYK 500 0.5 580 y 0.4 600 D65 white point 620 0.3

0.2

480 0.1

0.0 460 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 x

Comparison of some RGB and CMYK colour gamuts on a CIE 1931 xy chromaticity diagram

4.2.2 Conversion

Main article: Color translation

Color space conversion is the translation of the representation of a color from one basis to another. This typically occurs in the context of converting an image that is represented in one color space to another color space, the goal being to make the translated image look as similar as possible to the original.

4.2.3 RGB density

The RGB color model is implemented in diﬀerent ways, depending on the capabilities of the system used. By far the most common general-used incarnation as of 2006 is the 24-bit implementation, with 8 bits, or 256 discrete levels of color per channel. Any color space based on such a 24-bit RGB model is thus limited to a range of 256×256×256 ≈ 16.7 million colors. Some implementations use 16 bits per component for 48 bits total, resulting in the same gamut with a larger number of distinct colors. This is especially important when working with wide-gamut color spaces 46 CHAPTER 4. DAY 4

A comparison of the chromaticities enclosed by some color spaces.

(where most of the more common colors are located relatively close together), or when a large number of digital ﬁltering algorithms are used consecutively. The same principle applies for any color space based on the same color model, but implemented in diﬀerent bit depths.

4.2.4 Lists

Main article: List of color spaces and their uses

CIE 1931 XYZ color space was one of the ﬁrst attempts to produce a color space based on measurements of human color perception (earlier eﬀorts were by James Clerk Maxwell, König & Dieterici, and Abney at Imperial College)[1] and it is the basis for almost all other color spaces. The CIERGB color space is a linearly-related companion of CIE XYZ. Additional derivatives of CIE XYZ include the CIELUV, CIEUVW, and CIELAB. 4.2. COLOR SPACE 47

A comparison of CMYK and RGB color models. This image demonstrates the diﬀerence between how colors will look on a computer monitor (RGB) compared to how they will reproduce in a CMYK print process.

Generic

Main article: Color models RGB uses additive color mixing, because it describes what kind of light needs to be emitted to produce a given color. RGB stores individual values for red, green and blue. RGBA is RGB with an additional channel, alpha, to indicate transparency. Common color spaces based on the RGB model include sRGB, Adobe RGB, ProPhoto RGB, scRGB, and CIE RGB. CMYK uses subtractive color mixing used in the printing process, because it describes what kind of inks need to be applied so the light reflected from the substrate and through the inks produces a given color. One starts with a white substrate (canvas, page, etc.), and uses ink to subtract color from white to create an image. CMYK stores ink values for cyan, magenta, yellow and black. There are many CMYK color spaces for different sets of inks, substrates, and press characteristics (which change the dot gain or transfer function for each ink and thus change the appearance). YIQ was formerly used in NTSC (North America, Japan and elsewhere) television broadcasts for historical reasons. This system stores a luma value roughly analogous to (and sometimes incorrectly identified as)[2][3] luminance, along with two chroma values as approximate representations of the relative amounts of blue and red in the color. It is similar to the YUV scheme used in most video capture systems[4] and in PAL (Australia, Europe, except France, 48 CHAPTER 4. DAY 4

Additive color mixing: Three overlapping lightbulbs in a vacuum, adding together to create white.

which uses SECAM) television, except that the YIQ color space is rotated 33° with respect to the YUV color space and the color axes are swapped. The YDbDr scheme used by SECAM television is rotated in another way. YPbPr is a scaled version of YUV. It is most commonly seen in its digital form, YCbCr, used widely in video and image compression schemes such as MPEG and JPEG. xvYCC is a new international digital video color space standard published by the IEC (IEC 61966-2-4). It is based on the ITU BT.601 and BT.709 standards but extends the gamut beyond the R/G/B primaries speciﬁed in those standards. HSV (hue, saturation, value), also known as HSB (hue, saturation, brightness) is often used by artists because it is often more natural to think about a color in terms of hue and saturation than in terms of additive or subtractive color components. HSV is a transformation of an RGB colorspace, and its components and colorimetry are relative to the RGB colorspace from which it was derived. HSL (hue, saturation, lightness/luminance), also known as HLS or HSI (hue, saturation, intensity) is quite similar to HSV, with “lightness” replacing “brightness”. The diﬀerence is that the brightness of a pure color is equal to the brightness of white, while the lightness of a pure color is equal to the lightness of a medium gray. 4.2. COLOR SPACE 49

Subtractive color mixing: Three splotches of paint on white paper, subtracting together to turn the paper black.

Commercial

• Munsell color system

• Pantone Matching System (PMS)

• Natural Color System (NCS)

Special-purpose

• The RG Chromaticity space is used in computer vision applications. It shows the color of light (red, yellow, green etc.), but not its intensity (dark, bright).

• The TSL color space (Tint, Saturation and Luminance) is used in face detection.

Obsolete

Early color spaces had two components. They largely ignored blue light because the added complexity of a 3- component process provided only a marginal increase in ﬁdelity when compared to the jump from monochrome 50 CHAPTER 4. DAY 4

to 2-component color.

• RG for early Technicolor ﬁlm • RGK for early color printing

4.2.5 Absolute color space

In color science, there are two meanings of the term absolute color space:

• A color space in which the perceptual diﬀerence between colors is directly related to distances between colors as represented by points in the color space.[5][6] • A color space in which colors are unambiguous, that is, where the interpretations of colors in the space are colorimetrically deﬁned without reference to external factors.[7][8]

In this article, we concentrate on the second definition. CIEXYZ and sRGB are examples of absolute color spaces, as opposed to a generic RGB color space. A non-absolute color space can be made absolute by defining its relationship to absolute colorimetric quantities. For instance, if the red, green, and blue colors in a monitor are measured exactly, together with other properties of the monitor, then RGB values on that monitor can be considered as absolute. The L*a*b* is sometimes referred to as absolute, though it also needs a white point specification to make it so.[9] A popular way to make a color space like RGB into an absolute color is to define an ICC profile, which contains the attributes of the RGB. This is not the only way to express an absolute color, but it is the standard in many industries. RGB colors defined by widely accepted profiles include sRGB and Adobe RGB. The process of adding an ICC profile to a graphic or document is sometimes called tagging or embedding; tagging therefore marks the absolute meaning of colors in that graphic or document.

Conversion

Main article: Color translation

A color in one absolute color space can be converted into another absolute color space, and back again, in general; however, some color spaces may have gamut limitations, and converting colors that lie outside that gamut will not produce correct results. There are also likely to be rounding errors, especially if the popular range of only 256 distinct values per component (8-bit color) is used. One part of the definition of an absolute color space is the viewing conditions. The same color, viewed under different natural or artificial lighting conditions, will look different. Those involved professionally with color matching may use viewing rooms, lit by standardized lighting. Occasionally, there are precise rules for converting between non-absolute color spaces. For example, HSL and HSV spaces are defined as mappings of RGB. Both are non-absolute, but the conversion between them should maintain the same color. However, in general, converting between two non-absolute color spaces (for example, RGB to CMYK) or between absolute and non-absolute color spaces (for example, RGB to L*a*b*) is almost a meaningless concept.

Arbitrary spaces

A different method of defining absolute color spaces is familiar to many consumers as the swatch card, used to select paint, fabrics, and the like. This is a way of agreeing a color between two parties. A more standardized method of defining absolute colors is the Pantone Matching System, a proprietary system that includes swatch cards and recipes that commercial printers can use to make inks that are a particular color.

4.2.6 See also

• Color theory 4.3. COLORCHECKER 51

• Color model

• List of colors

4.2.7 References

[1] William David Wright, 50 years of the 1931 CIE Standard Observer. Die Farbe, 29:4/6 (1981).

[2] Charles Poynton, “YUV and 'luminance' considered harmful: a plea for precise terminology in video,” online, author-edited version of Appendix A of Charles Poynton, Digital Video and HDTV: Algorithms and Interfaces, Morgan–Kaufmann, 2003. online

[3] Charles Poynton, Constant Luminance, 2004

[4] Dean Anderson. “Color Spaces in Frame Grabbers: RGB vs. YUV”. Retrieved 2008-04-08.

[5] Hans G. Völz (2001). Industrial Color Testing: Fundamentals and Techniques. Wiley-VCH. ISBN 3-527-30436-3.

[6] Gunter Buxbaum; Gerhard Pfaﬀ (2005). Industrial Inorganic Pigments. Wiley-VCH. ISBN 3-527-30363-4.

[7] Jonathan B. Knudsen (1999). Java 2D Graphics. O'Reilly. ISBN 1-56592-484-3.

[8] Bernice Ellen Rogowitz; Thrasyvoulos N Pappas; Scott J Daly (2007). Human Vision and Electronic Imaging XII. SPIE. ISBN 0-8194-6605-0.

[9] Yud-Ren Chen; George E. Meyer; Shu-I. Tu (2005). Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality. SPIE. ISBN 0-8194-6020-6.

3. www.iscc.org/aic2001/abstracts/poster/Zoch.doc

4.2.8 External links

• Color FAQ, Charles Poynton

• FAQ about color physics, Stephen Westland

• Color Science, Dan Bruton

• Color Spaces, Rolf G. Kuehni (October 2003)

• Colour spaces – perceptual, historical and applicational background, Marko Tkalčič (2003)

• Color formats for image and video processing – Color conversion between RGB, YUV, YCbCr and YPbPr.

• C library of SSE-optimised color format conversions.

• Konica Minolta Sensing: Precise Color Communication

4.3 ColorChecker

Nominal chromaticities of ColorChecker patches in the CIE 1931 xy chromaticity diagram (in the SVG version, hover over a color swatch to highlight it; click it to select and deselect it)

The ColorChecker Color Rendition Chart (often referred to by its original name, the Macbeth ColorChecker[1] or simply Macbeth chart[2]) is a color calibration target consisting of a cardboard-framed arrangement of 24 squares of painted samples. The ColorChecker was introduced in a 1976 paper by McCamy, Marcus, and Davidson in the Journal of Applied Photographic Engineering.[3] The chart’s color patches have spectral reflectances intended to mimic those of natural objects such as human skin, foliage, and flowers, to have consistent color appearance under a variety of lighting conditions, especially as detected by typical color photographic film, and to be stable over time. 52 CHAPTER 4. DAY 4

ColorChecker held in a photographic portrait setting

4.3.1 Design

The ColorChecker chart is a rectangular card measuring about 11 × 8.25 inches, or in its original incarnation about 13 × 9 in., an aspect ratio approximately the same as that of 35 mm ﬁlm.[4] It includes 24 patches in a 4 × 6 grid, each slightly under 2 inches square, made of matte paint applied to smooth paper, and surrounded by a black border. Six of the patches form a uniform gray lightness scale, and another six are primary colors typical of chemical photographic processes – red, green, blue, cyan, magenta, and yellow. The remaining colors include approximations of medium light and medium dark human skin, blue sky, the front of a typical leaf, and a blue chicory ﬂower. The rest were chosen arbitrarily to represent a gamut “of general interest and utility for test purposes”, though the orange and yellow patches are similarly colored to typical oranges and lemons.[3]

4.3.2 Colors

The colors of the chart were described by McCamy et al. with colorimetric measurements using the CIE 1931 2° standard observer and Illuminant C, and also in terms of the Munsell color system. Using measured reﬂectance [5] spectra, it is possible to derive CIELAB coordinates for Illuminants D65 and D50 and coordinates in sRGB.

Table from Field (1990); CIE data for Illuminant C from Poynton (2008).[4][6]

4.3.3 Use

Color targets such as the ColorChecker can be captured by cameras and other color input devices, and the resulting images’ output can be compared to the original chart, or to reference measurements, to test the degree to which image 4.3. COLORCHECKER 53 acquisition reproduction systems and processes approximate the human visual system’s. Because of its wide avail- ability and use, its careful design, and its consistency, and because comprehensive spectrophotometric measurements are available, the ColorChecker has also been used in academic research into topics such as spectral imaging.[8]

4.3.4 ColorChecker Digital SG

X-Rite also sells a 140-patch chart called the ColorChecker Digital SG, and is intended for automated use with computer software to characterize digital cameras and scanners.

4.3.5 See also

• List of colors • Color chart • Color calibration • Color management • Color mapping • ICC proﬁle • IT8

4.3.6 References

[1] The ColorChecker was originally produced by Macbeth (then a subsidiary of Kollmorgen), which through a series of mergers and acquisitions now belongs to X-Rite.

[2] “Computational Color Imaging - Alain Trémeau - Google Books”. Retrieved 12 October 2015.

[3] C. S. McCamy, H. Marcus, and J. G. Davidson (1976). “A Color-Rendition Chart”. Journal of Applied Photographic Engineering 2(3). 95–99.

[4] Charles Poynton (2008). “ColorChecker (‘Macbeth’) Chart”. poynton.com

[5] Measured reﬂectance spectra are available from the Munsell Color Science Laboratory website in html and Excel formats, taken from measurements published in Noboru Ohta (1997). “The Basis of Color Reproduction Engineering” (Japanese). Corona-sha Company of Japan. See also Danny Pascale’s page.

[6] Field, Gary G. (1990), Color Scanning and Imaging Systems, Pittsburg, PA: Graphic Arts Technical Foundation, ISBN 0-88362-120-7

[7] ColorChecker Colorimetric Data (PDF), archived from the original (PDF) on 2012-04-17, retrieved 2012-04-17

[8] For example, Roy S. Berns and Lawrence A. Taplin (2006). “Practical Spectral Imaging Using a Color-Filter Array Digital Camera”.

4.3.7 External links

• “ColorChecker Classic” oﬃcial product page at the X-Rite website. • “ColorChecker Digital SG” product page • Danny Pascale (2009). “The ColorChecker (since 1976!)". Babelcolor.com. This extensive page includes a history of the chart, average spectrophotometric measurements from 20 ColorCheckers (the precise tools used for these measurements is unclear), calculated RGB values in a variety of RGB color spaces, a list of places to buy charts, and advice for using the data in practical camera calibration and image applications. • Danny Pascale (2006) “RGB coordinates of the Macbeth ColorChecker”. Includes comparisons in CIELAB and RGB values based on spectrophotometric measurements vs. provided by Gretag–Macbeth 54 CHAPTER 4. DAY 4

• Bruce Lindbloom (2007). “How the ColorChecker Calculator Works”. brucelindbloom.com. Lindbloom measured the spectral reﬂectances his own copy of the ColorChecker, and created a Java applet to calculate colorimetric coordinates under various standard illuminants and in various RGB color spaces

• Bruce Lindbloom (2008). “ColorChecker RGB Summaries, Spreadsheets and Lab TIFF File”. brucelindbloom.com. A page showing RGB values for color patches in various RGB color spaces, based on the applet described above, and a set of Excel spreadsheets for comparing these numbers to those in a digital camera or scanner image of the ColorChecker. Chapter 5

Day 5

5.1 Primary color

This article is about colors. For other uses, see Primary Colors. A set of primary colors is a small, arbitrary set of pigmented physical media, lights or purely abstract elements of a

The emission spectra of the three phosphors that define the additive primary colors of a CRT color video display. Other electronic color display technologies (LCD, Plasma display, OLED) have analogous sets of primaries with different emission spectra. mathematical colorspace model. Distinct colors from a larger gamut can be specified in terms of a mixture of primary colors which facilitates technological applications such as painting, electronic displays and printing. Any small set of pigments or lights are “imperfect” physical primary colors in that they cannot be mixed to yield all possible colors that can be perceived by the human color vision system. The abstract (or “imaginary”) primaries X, Y and Z of the CIEXYZ colorspace can be mathematically summed to specify essentially all colors that can be perceived but these primaries cannot be physically realized due to the underlying structure and overlapping spectral sensitivities of each of the human cone photoreceptors.[1] The precise set of primary colors that are used in a specific color application depend on gamut requirements as well as application-specific constraints such as cost, power consumption, lightfastness, mixing behavior etc.

55 56 CHAPTER 5. DAY 5

In an additive set of colors, as in coincident projected lights or in electronic visual displays, the primary colors normally used are red, green and blue (but the precise visible light spectra for each color can vary signiﬁcantly). In a subtractive set of colors, as in mixing of pigments or dyes for printing, the colors magenta, yellow and cyan are normally used.[2] See RGB color model, and CMYK color model for more on these popular sets of primary colors.

5.1.1 Biological basis

Population Weighted Cone Spectral Sensitivities

0.6 L

0.4 cone sensitivity 0.2 M

S

0.0

400 500 600 wavelength (nm)

Population weighted cone spectral sensitivities that emphasize no visible wavelength of light stimulates only one color photoreceptor type.

Primary colors are not a fundamental property of light but are related to the color vision system in animals. The human eye normally contains only three types of color photoreceptors (L, M and S) that are associated with specialized cone cells. Each photoreceptor responds to different ranges of the visible electromagnetic spectrum and there is no single wavelength that stimulates only one photoreceptor type. Humans and other species with three such types of color photoreceptor are known as trichromats. In spite of color being a complex psychophysical response to electromagnetic radiation, controlled color matching experiments (e.g., CIE 1931) have essentially mapped all possible colors the eye can see in terms of the response of each of the three color photoreceptors, which correspond to the three dimensions of CIEXYZ. Color appearance models like CIECAM02 describe color more generally in six dimensions and can be used to predict how colors appear in different viewing conditions. Most placental mammals other than primates have only two types of color photoreceptor and are therefore dichromats 5.1. PRIMARY COLOR 57 while birds and marsupials are tetrachromats with four color photoreceptor types. There is no currently peer reviewed scholarly work that has confirmed the existence of a functional human tetrachromat though they are suspected to exist.[3] It may seem that the primary colors of an animal’s vision system corresponds to the number of color photoreceptor types but the mere presence of “extra” photoreceptor types does not directly imply that they are being used functionally. Demonstrating improved spectral discrimination in any animal can be difficult since complex sets of neurons affect color perception in ways that are generally difficult to interrogate.[4]

5.1.2 History

Before the nature of colorimetry and visual physiology were well understood a number of color models assigned primary colors to diﬀerent hues (e.g. the RYB model). Scientists such as Thomas Young, James Clerk Maxwell and Hermann von Helmholtz expressed various opinions about what should be the three primary colors to describe the three primary color sensations of the eye.[5] Young originally proposed red, green and violet, and Maxwell changed violet to blue; Helmholtz proposed “a slightly purplish red, a vegetation-green, slightly yellowish, and an ultramarine- blue.[6] In modern understanding, human cone cells do not correspond precisely to a speciﬁc set of primary colors, as each cone type responds to a relatively broad range of wavelengths.

5.1.3 Examples

A self portrait by Anders Zorn clearly showing a four pigment palette of what are thought to be white, yellow ochre, red vermilion and black pigments.[7] 58 CHAPTER 5. DAY 5

A photograph of the red, green and blue pixels of an LCD display.

The cyan, magenta, yellow and black (key) (CMYK) inks found in an inkjet printer that can be used for color photographic reproduction.

Limited palettes in visual art

There are hundreds of commercially available pigments for visual artists to use and mix (in various media such as oil, watercolor, acrylic and pastel). A common approach is to use just a limited palette of pigments (often between four and eight) that can be physically mixed to any color that the artist desires in the final work. There are no specific set of pigments that are primary colors, the choice of pigment depends entirely on the artist’s subjective preference of subject and style of art as well as material considerations like lightfastness and mixing heuristics. Contemporary classical realists have often advocated that a limited palette of white, red, yellow and black pigment (often described as the “Zorn palette”) is sufficient for compelling work.[8] 5.1. PRIMARY COLOR 59

RGB for electronic displays

Main articles: Additive color and RGB color model

Media that combine emitted lights to create the sensation of a range of colors are using the additive color system. The primary colors used in most electronic displays are typically saturated red, green and blue light.[9] The exact colors chosen for the primaries are a technological compromise between the available phosphors (including considerations such as cost and power usage) and the need for large color triangle to allow a large gamut of colors. The ITU-R BT.709-5/sRGB primaries are typical. Additive mixing of red and green light produces shades of yellow, orange, or brown.[10] Mixing green and blue produces shades of cyan, and mixing red and blue produces shades of purple, including magenta. Mixing nominally equal proportions of the additive primaries results in shades of grey or white; the color space that is generated is called an RGB color space. The experiments used to derive the CIE 1931 colorspace used monochromatic primary colored lights with the (arbitrary) wavelengths of 435.8 nm (violet), 546.1 nm (green) and 700 nm (red) due to the convenience they aﬀorded to the experimental work.

Recent developments Some recent TV and computer displays are starting to include yellow as a fourth primary color, often in a four-point square pixel area, so as to achieve brighter pure yellows and a larger color gamut.[11] Even the four-primary technology does not yet reach the range of colors that the human eye can see from light reflected by illuminated surfaces (as defined by the sample-based estimate called the Pointer Gamut[12]), with 4-primary LED prototypes providing typically about 87% and 5-primary prototypes about 95%. Several firms, including Sam- sung and Mitsubishi, have demonstrated LED displays with five or six “primaries”, or color LED point light sources per pixel.[13][14] A recent academic literature review claims a gamut of 99% can be achieved with 5-primary LED technology.[15] While technology for achieving a wider gamut appears to be within reach, other issues remain; for example, affordability, dynamic range, and brilliance. In addition, there exists hardly any source material recorded in this wider gamut, nor is it currently possible to recover this information from existing visual media. Regardless, industry is still exploring a wide variety of “primary” active light sources (per pixel) with the goal of matching the capability of human color perception within a broadly affordable price. One example of a potentially affordable but yet unproven active light hybrid places an LED screen over a plasma light screen, each with different “primaries”. Because both LED and plasma technologies are many decades old (plasma pixels going back to the 1960s), both have become so affordable that they could be combined.

CMYK color model or four-color printing

Main article: CMYK color model

In the printing industry, the subtractive primaries cyan, magenta and yellow are applied together in varying amounts for useful gamuts. An additional key ink (shorthand for the key printing plate that impressed the artistic detail of an image, usually in black ink.[16]) is also usually used since it is diﬃcult to mix a dark enough black ink using the other three inks as well as other practical considerations such as cost and ink bleed. Before the color names cyan and magenta were in common use, these primaries were often known as blue-green and purple or in some circles as blue and red, respectively, and their exact color has changed over time with access to new pigments and technologies.[17]

Psychological primaries

Main article: Opponent process See also: Natural Color System and Unique hues

The opponent process is a color theory that states that the human visual system interprets information about color by processing signals from cones and rods in an antagonistic manner. The three types of cones have some overlap in the wavelengths of light to which they respond, so it is more eﬃcient for the visual system to record diﬀerences between the responses of cones, rather than each type of cone’s individual response. The opponent color theory suggests that there are three opponent channels: red versus green, blue versus yellow and black versus white.[18] Responses to one color of an opponent channel are antagonistic to those of the other color. The theory states that the particular colors considered by an observer to be uniquely representative of the concepts red, yellow, green, blue, white and 60 CHAPTER 5. DAY 5

Approximations within the sRGB gamut to the “aim colors” of the Natural Color System, a model based on the opponent process theory of color vision. black might be called “psychological primary colors”, because any other color could be described in terms of some combination of these.

5.1.4 See also

• Color vision

5.1.5 References

[1] Bruce MacEvoy. “Do 'Primary' Colors Exist?" (Material Trichromacy section). Handprint. Accessed 10 August 2007.

[2] Matthew Luckiesh (1915). Color and Its Applications. D. Van Nostrand company. pp. 58, 221.

[3] Greenwood, Veronique. “The Humans With Super Human Vision”. Discover Magazine. Kalmbach Publishing Co. Re- trieved 29 September 2016.

[4] Morrison, Jessica (23 January 2014). “Mantis shrimp’s super colour vision debunked”. Nature. doi:10.1038/nature.2014.14578.

[5] Edward Albert Sharpey-Schäfer (1900). Text-book of physiology. 2. Y. J. Pentland. p. 1107.

[6] Alfred Daniell (1904). A text book of the principles of physics. Macmillan and Co. p. 575.

[7] Nyholm, Arvid (1914). “Anders Zorn: The Artist and the Man”. Fine Arts Journal. 31 (4): 469. doi:10.2307/25587278.

[8] Gurney. “The Zorn Palette”. Gurney Journey. Retrieved 27 September 2016.

[9] Thomas D. Rossing & Christopher J. Chiaverina (1999). Light science: physics and the visual arts. Birkhäuser. p. 178. ISBN 978-0-387-98827-6.

[10] “Some Experiments on Color”, Nature 111, 1871, in John William Strutt (Lord Rayleigh) (1899). Scientiﬁc Papers. Uni- versity Press. 5.2. TERTIARY COLOR 61

[11] Garvey, Jude (2010-01-20). “Sharp four primary color TVs enable over one trillion colors”. gizmag.com.

[12] M. R. Pointer (1980). “The Gamut of Real Surface Colours”. Color Research and Application. John Wiley & Sons, Inc. 5 (3): 145–155. doi:10.1002/col.5080050308.

[13] Chih-Cheng Chan; Guo-Feng Wei; Hui Chu-Ke; Sheng-Wen Cheng; Shih-Chang Chu; Ming-Sheng Lai; Arex Wang; Shmuel Roth; Oded Ben David; Moshe Ben Chorin; Dan Eliav; Ilan Ben David (1999). Development of Multi-Primary Color LCD. AU Optronics, Science-Based Industrial Park, Hsin-Chu, Taiwan; Genoa Color Technologies, Herzelia, Israel.

[14] Thomas Rossing; Christopher J Chiaverina (24 September 1999). Light Science: Physics and the Visual Arts. Springer Science & Business Media. pp. 178–. ISBN 978-0-387-98827-6.

[15] Abhinav Priya (2011), Five-Primary Color LCD (PDF), Cochin University of Science and Technology, Department of Electronics Engineering, p. 2

[16] Frank S. Henry (1917). Printing for School and Shop: A Textbook for Printers’ Apprentices, Continuation Classes, and for General use in Schools. John Wiley & Sons.

[17] Ervin Sidney Ferry (1921). General Physics and Its Application to Industry and Everyday Life. John Wiley & Sons.

[18] Michael Foster (1891). A Text-book of physiology. Lea Bros. & Co. p. 921.

5.2 Tertiary color

A tertiary color is a color made by mixing full saturation of one primary color with half saturation of another primary color and none of a third primary color, in a given color space such as RGB,[1] CMYK (more modern) or RYB[2] (traditional). Tertiary colors have speciﬁc names, one set of names for the RGB color wheel and a diﬀerent set for the RYB color wheel. These names are shown below. Brown and grey colors can be made by mixing complementary colors.

5.2.1 RGB or CMY primary, secondary, and tertiary colors

The primary colors in an RGB color wheel are red, green, and blue, because these are the three additive colors—the primary colors of light. The secondary colors in an RGB color wheel are cyan, magenta, and yellow because these are the three subtractive colors—the primary colors of pigment. The tertiary color names used in the descriptions of RGB (or equivalently CMYK) systems are shown below.

5.2.2 Traditional painting (RYB)

The primary colors in an RYB color wheel are red, yellow, and blue. The secondary colors — orange, green, and purple — are made by combining the primary colors In the red–yellow–blue system as used in traditional painting and interior design, tertiary colors are typically named by combining the names of the adjacent primary and secondary.[3][4]

Tertiary- and quaternary-color terms

The terms for the RYB tertiary colors are not set. For the six RYB hues intermediate between the RYB primary and secondary colors, the names amber/marigold (yellow–orange), vermilion/cinnabar (red–orange), magenta (red– purple), violet (blue–purple), teal/aqua (blue-green), and chartreuse/lime green (yellow–green) are commonly found. The names for the twelve quaternary colors are more variable, if they exist at all, though indigo and scarlet are standard for blue–violet and red–vermilion. In another sense, a tertiary color is obtained by mixing secondary-colored pigments. These three colors are russet (orange–purple), slate (purple–green), and citron (green–orange), with the corresponding three quaternary colors plum (russet–slate), sage (slate–citron), buﬀ (citron–russet) (with olive sometimes used for either slate or citron).[6][7] Beyond that are shades of grey (blue grey and brown greys), which approach but never quite reach black. 62 CHAPTER 5. DAY 5

The RYB color terminology outlined above and in the color samples shown below is ultimately derived from an 1835 book called “Chromatography”, an analysis of the RYB color wheel by George Field, a chemist who specialized in pigments and dyes.[8]

5.2.3 Comparison of RGB and RYB color wheels

Unlike the RGB (CMY) color wheel, the RYB color wheel has no scientiﬁc basis. The RYB color wheel was invented centuries before the 1890s, when it was found by experiment that magenta, yellow, and cyan are the primary colors of pigment, not red, yellow, and blue. The RGB (CMY) color wheel has largely replaced the traditional RYB color wheel because it is possible to display much brighter and more saturated colors using the primary and secondary colors of the RGB (CMY) color wheel. In the terminology of color theory, RGB color space (CMY color space) has a much larger color gamut than RYB color space.

5.2.4 See also

• Color wheel

• Color theory

5.2.5 References

[1] Marcus Weise and Diana Weynand (2007). How Video Works. Focal Press. ISBN 0-240-80933-5.

[2] Stan Place and Bobbi Ray Madry (1990). The Art and Science of Professional Makeup. Thomson Delmar Learning. ISBN 0-87350-361-9.

[3] Adrienne L. Zihlman (2001). The Human Evolution Coloring Book. HarperCollins. ISBN 0-06-273717-1.

[4] Kathleen Lochen Staiger (2006). The Oil Painting Course You've Always Wanted: Guided Lessons for Beginners and Expe- rienced Artists. Watson-Guptill. ISBN 0-8230-3259-0.

[5] Susan Crabtree and Peter Beudert (1998). Scenic Art for the Theatre: History, Tools, and Techniques. Focal Press. ISBN 0-240-80187-3.

[6] William J. Miskella, 1928, Practical Color Simpliﬁed: A Handbook on Lacquering, Enameling, Coloring And Painting, pp

[7] John Lemos, 1920, “Color Charts for the School Room”, in School Arts, vol. 19, pp 580–584

[8] Maerz and Paul A Dictionary of Color New York:1930 Page 154

[9] RGB approximations of RYB tertiary colors, using cubic interpolation. The colors are paler than a simple mixture of paints would produce. For the darker, true secondary colors, see secondary color. Pure tertiary colors would be darker still. 5.2. TERTIARY COLOR 63

Page from A New Practical Treatise on the Three Primitive Colours Assumed as a Perfect System of Rudimentary Information by Charles Hayter 64 CHAPTER 5. DAY 5

Red Rose Orange

Magenta Yellow

Chartreuse Violet Green

Blue Green

Azure Spring Green Cyan

Primary, secondary, and tertiary colors of the RGB color wheel 5.2. TERTIARY COLOR 65

Red Magenta Vermilion

Purple Orange

Violet Amber

Blue Yellow

Teal Chartreuse Green

A traditional RYB color wheel. 66 CHAPTER 5. DAY 5

5.3 Additive color

Additive color mixing: adding red to green yields yellow; adding all three primary colors together yields white.

Additive color is color created by mixing a number of different light colors, with shades of red, green, and blue being the most common primary colors used in additive color system. Additive color is in contrast to subtractive color, in which colors are created by subtracting (absorbing) parts of the spectrum of light present in ordinary white light, by means of colored pigments or dyes, such as those in paints, inks, and the three dye layers in typical color photographs on film. The combination of two of the standard three additive primary colors in equal proportions produces an additive secondary color—cyan, magenta or yellow—which, in the form of dyes or pigments, are the standard primary colors in subtractive color systems. The subtractive system using primaries that are the secondaries of the additive system can be viewed as an alternative approach to reproducing a wide range of colors by controlling the relative amounts of red, green, and blue light that reach the eye. Computer monitors and televisions are the most common examples of additive color. Examination with a sufficiently powerful magnifying lens will reveal that each pixel in CRT, LCD and most other types of color video displays is composed of red, green and blue sub-pixels, the light from which combines in various proportions to produce all the other colors as well as white and shades of gray. The colored sub-pixels do not overlap on the screen, but when viewed from a normal distance they overlap and blend on the eye’s retina, producing the same result as external 5.3. ADDITIVE COLOR 67

James Clerk Maxwell, with his color top that he used for investigation of color vision and additive color superimposition. Another example of additive color can be found in the overlapping projected colored lights often used in theatrical lighting for plays, concerts, circus shows and night clubs.[1] The full gamut of color available in any additive color system is defined by all the possible combinations of all the possible luminosities of each primary color in that system. In chromaticity space, the gamut is a plane convex polygon with corners at the primaries. For three primaries, it is a triangle. Results obtained when mixing additive colors are often counterintuitive for people accustomed to the subtractive color 68 CHAPTER 5. DAY 5 system of pigments, dyes, inks and other substances that present color to the eye by reflection rather than emission. For example, in subtractive color systems, green is a combination of yellow and cyan; in additive color, red plus green makes yellow. Additive color is a result of the way the eye detects color, and is not a property of light. There is a vast difference between a pure spectral yellow light, with a wavelength of approximately 580 nm, and a mixture of red and green light. However, both stimulate our eyes in a similar manner, so we do not detect that difference, and both are yellow light to the human eye. (see eye (cytology), color vision.)

5.3.1 History

The ﬁrst permanent color photograph, taken by Thomas Sutton, under the direction of James Clerk Maxwell in 1861.

Systems of additive color are motivated by the Young–Helmholtz theory of trichromatic color vision, which was articulated around 1850 by Hermann von Helmholtz, based on earlier work by Thomas Young. For his experimental work on the subject, James Clerk Maxwell is sometimes credited as being the father of additive color.[2] He had the photographer Thomas Sutton photograph a tartan ribbon on black-and-white film three times, first with a red, then green, then blue color filter over the lens. The three black-and-white images were developed and then projected onto a screen with three different projectors, each equipped with the corresponding red, green, or blue color filter used to take its image. When brought into alignment, the three images (a black-and-red image, a black-and-green image and a black-and-blue image) formed a full color image, thus demonstrating the principles of additive color.[3]

5.3.2 Examples

The following chart demonstrates an example of the mixing and perception of additive primaries, step by step. To fully understand the process, it should be demonstrated how dull colors are obtained using cyan, magenta, and yellow instead of red, green, and blue. 5.3. ADDITIVE COLOR 69

Red, green, and blue lights combining by reﬂecting from a white wall.

5.3.3 See also

• Color mixing

• Color space

• Color theory

• Color motion picture ﬁlm

• Kinemacolor

• Prizma Color

• RGB color model

• Subtractive color

• Technicolor

• William Friese-Greene

5.3.4 References

[1] David Briggs (2007). “The Dimensions of Color”. Retrieved 2011-11-23.

[2] “James Clerk Maxwell”. Inventor’s Hall of Fame, Rochester Institute of Technology Center for Imaging Science.

[3] Robert Hirsch (2004). Exploring Colour Photography: A Complete Guide. Laurence King Publishing. ISBN 1-85669-420- 8. 70 CHAPTER 5. DAY 5

Additive mixing of primary colors by proximity: red, green, and blue lines brought close together create mixed colors (click image to enlarge and see the eﬀect clearly).

5.3.5 External links

• RGB and CMYK Colour systems. • http://www.edinphoto.org.uk/1_P/1_photographers_maxwell.htm - Photos and stories from the James Clerk Maxwell Foundation. • Stanford University CS 178 interactive Flash demo comparing additive and subtractive color mixing. 5.4. SUBTRACTIVE COLOR 71

Additive color mixing

5.4 Subtractive color

A subtractive color model explains the mixing of a limited set of dyes, inks, paint pigments or natural colorants to create a wider range of colors, each the result of partially or completely subtracting (that is, absorbing) some wavelengths of light and not others. The color that a surface displays depends on which parts of the visible spectrum are not absorbed and therefore remain visible. Subtractive color systems start with light, presumably white light. Colored inks, paints, or filters between the watchers and the light source or reflective surface subtract wavelengths from the light, giving it color. If the incident light is other than white, our visual mechanisms are able to compensate well, but not perfectly, often giving a flawed impression of the “true” color of the surface. Conversely, additive color systems start with darkness. Light sources of various wavelengths are added in various proportions to produce a range of colors. Usually, three primary colors are combined to stimulate humans’ trichromatic color vision, sensed by the three types of cone cells in the eye, giving an apparently full range.

5.4.1 RYB

Main article: RYB color model

RYB (Red, Yellow, Blue) is the formerly standard set of subtractive primary colors used for mixing pigments. It is used in art and art education, particularly in painting. It predated modern scientiﬁc color theory. Red, yellow, and blue are the primary colors of the standard color “wheel”. The secondary colors, violet (or purple), orange, and green (VOG) make up another triad, formed by mixing equal amounts of red and blue, red and yellow, and blue and yellow, respectively. The RYB primary colors became the foundation of 18th century theories of color vision as the fundamental sensory 72 CHAPTER 5. DAY 5

Subtractive color mixing qualities blended in the perception of all physical colors and equally in the physical mixture of pigments or dyes. These theories were enhanced by 18th-century investigations of a variety of purely psychological color eﬀects, in particular the contrast between “complementary” or opposing hues produced by color afterimages and in the contrasting shadows in colored light. These ideas and many personal color observations were summarized in two founding documents in color theory: the Theory of Colors (1810) by the German poet and government minister Johann Wolfgang von Goethe, and The Law of Simultaneous Color Contrast (1839) by the French industrial chemist Michel-Eugène Chevreul. In late 19th and early to mid-20th century commercial printing, use of the traditional RYB terminology persisted even though the more versatile CMY (Cyan, Magenta, Yellow) triad had been adopted, with the cyan sometimes referred to as “process blue” and the magenta as “process red”.

5.4.2 CMY and CMYK printing processes

Main article: CMYK color model

In color printing, the usual primary colors are cyan, magenta and yellow (CMY). Cyan is the complement of red, meaning that the cyan serves as a ﬁlter that absorbs red. The amount of cyan applied to a white sheet of paper controls how much of the red in white light will be reﬂected back from the paper. Ideally, the cyan is completely 5.4. SUBTRACTIVE COLOR 73

An 1877 color photo by Louis Ducos du Hauron, a French pioneer of color photography. The overlapping subtractive yellow, cyan and red (magenta) image elements can be seen clearly along the edges of the image. transparent to green and blue light and has no effect on those parts of the spectrum. Magenta is the complement of green, and yellow the complement of blue. Combinations of different amounts of the three can produce a wide range of colors with good saturation. In inkjet color printing and typical mass production photomechanical printing processes, a black ink K (Key) component is included, resulting in the CMYK color model. The black ink serves to cover unwanted tints in dark areas of the printed image, which result from the imperfect transparency of commercially practical CMY inks; to improve image sharpness, which tends to be degraded by imperfect registration of the three color elements; and to reduce or eliminate consumption of the more expensive color inks where only black or gray is required. Purely photographic color processes almost never include a K component, because in all common processes the CMY dyes used are much more perfectly transparent, there are no registration errors to camouflage, and substituting a black dye for a saturated CMY combination, a trivial prospective cost benefit at best, is technologically impractical in non-electronic analog photography.

5.4.3 See also

• Additive color

• Color mixing

• Color motion picture ﬁlm

• Color space

• Color theory

• Primary color 74 CHAPTER 5. DAY 5

Standard RYB Color Wheel

5.4.4 References

• Berns, Roy S. (2000). Billmeyer and Saltzman’s Principles of Color Technology, 3rd edition. Wiley, New York. ISBN 0-471-19459-X.

• Stroebel, Leslie, John Compton, Ira Current, and Richard Zakia (2000). Basic Photographic Materials and Processes, 2nd edition. Focal Press, Boston. ISBN 0-240-80405-8.

• Wyszecki, Günther & W. S. Stiles (1982). Colour Science: Concept and Methods, Quantitative Data and Formulae. Wiley, New York. ISBN 0-471-02106-7.

5.4.5 External links

• Stanford University CS 178 interactive Flash demo comparing additive and subtractive color mixing. 5.5. COLOR MIXING 75

White light split by a prism. The additive primary colors are clearly visible.

5.5 Color mixing

There are two types of color mixing: Additive and Subtractive. In both cases there are three primary colors, three secondary colors (colors made from 2 of the three primary colors in equal amounts), and one tertiary color made from all three primary colors. This point is a common source of confusion, as there are diﬀerent sets of primary colors depending on whether you are working with additive or subtractive mixing.

5.5.1 Additive Mixing

Main article: Additive color

The additive mixing of colors is unintuitive as it does not correspond to the mixing of physical substances (such as paint) which would correspond to subtractive mixing. For instance, one can additively mix yellow and blue by shining yellow light together with blue light, which will result in not green but a pinkish light. As in this example, one should always have the mixture of light in mind when considering additive color mixing as it is the only situation where it occurs. Despite being unintuitive, it is conceptually simpler than subtractive mixing. Two beams of light that are superimposed correspond to additive mixing. By convention, the three primary colors in additive mixing are red, green, and blue. In the absence of color or, when no colors are showing, the result is black. If all three primary colors are showing, the result is white. When red and green combine, the result is yellow. When red and blue combine, the result is magenta. When blue and green combine, the result is cyan. Additive mixing is used in television and computer monitors to produce a wide range of colors using only three 76 CHAPTER 5. DAY 5

A simulated example of additive color mixing primary colors. A pixel is a juxtaposition of these three primary colors. Projection televisions typically have three projectors, one for each primary color.

5.5.2 Subtractive Mixing

Main article: Subtractive color

The mixing of colored physical substances corresponds to subtractive color mixing, hence it corresponds to our in- tuition about mixing colors. To explain the mechanism, let us consider mixing red paint with yellow paint. The red paint is red because when the ambient light strikes it, the composition of the material is such that it absorbs all other colors in the visible spectrum except for red. The red light, not being absorbed, reflects off the paint and is what we see. This same mechanism describes the color of all material objects -- note that light is not a material object -- and so applies to the yellow paint as well. Making recourse to the figure above demonstrating additive color mixing, one sees that yellow light is composed of a(n additive) mixture of red and green light. When we mix the two paints, the resulting substance has red paint and yellow paint. The yellow paint absorbs all colors except for red and green. However, the red paint will absorb the green reflected by the yellow paint. The red paint can be said to subtract the green from the yellow paint. The resulting paint reflects only red light and so appears red to our eyes. Note however that this description is theoretical and that the mixing of pigments does not correspond to ideal subtractive color mixing because some light from the subtracted color is still being reflected by one component of the original paint. This results in a darker and desaturated color compared to the color that would be achieved with ideal filters. By convention, the three primary colors in subtractive mixing are yellow, magenta and cyan; however, for a long time painters have used yellow, red and blue in place of these. In subtractive mixing of color, the absence of color is white and the presence of all three primary colors is black. The secondary colors are the same as the primary colors from additive mixing, and vice versa. This is not an accident. By mixing additive secondary colors subtractively one can reachieve the primary additive colors. Subtractive mixing is used to create a variety of colors when printing on paper by combining a small number of ink colors, and also when painting. Green is a part of mixing yellow and blue. 5.5. COLOR MIXING 77

A simulated example of subtractive color mixing

Orange is a part of mixing red and yellow. Purple is a part of mixing blue and red.

5.5.3 See also

• Color theory

• Subtractive color

• Additive color

• Impossible colors

5.5.4 External links

• Interactive Java applet on the additive mixing of RGB colors by Wolfgang Bauer

• Interactive Java applet on the subtractive mixing of CYM colors by Wolfgang Bauer 78 CHAPTER 5. DAY 5

5.5.5 References

• Macaulay, David and Neil Ardley (1988). The New Way Things Work. London: Dorling Kindersley Ltd. ISBN 0-395-93847-3. Chapter 6

Day 6

6.1 Color calibration

The aim of color calibration is to measure and/or adjust the color response of a device (input or output) to a known state. In International Color Consortium (ICC) terms, this is the basis for an additional color characterization of the device and later profiling.[1] In non-ICC workflows, calibration refers sometimes to establishing a known relationship to a standard color space[2] in one go. The device that is to be calibrated is sometimes known as a calibration source; the color space that serves as a standard is sometimes known as a calibration target. Color calibration is a requirement for all devices taking an active part of a color-managed workflow. Color calibration is used by many industries, such as television production, gaming, photography, engineering, chemistry, medical and more.

6.1.1 Information ﬂow and output distortion

Input data can come from device sources like digital cameras, image scanners or any other measuring devices. Those inputs can be either monochrome (in which case only the response curve needs to be calibrated, though in a few select cases one must also specify the color or spectral power distribution that that single channel corresponds to) or specified in multidimensional color - most commonly in the three channel RGB model. Input data is in most cases calibrated against a profile connection space (PCS).[3] One of the most important factors to consider when dealing with color calibration is having a valid source. If the color measuring source does not match the displays capabilities, the calibration will be ineffective and give false readings. The main distorting factors on the input stage stem from the amplitude nonlinearity of the channel response(s), and in the case of a multidimensional datastream the non-ideal wavelength responses of the individual color separation filters (most commonly a color filter array (CFA)) in combination with the spectral power distribution of the scene illumination. After this the data is often circulated in the system translated into a working space RGB for viewing and editing. In the output stage when exporting to a viewing device such as a CRT or LCD screen or a digital projector, the computer sends a signal to the computer’s graphic card in the form RGB [Red,Green,Blue]. The dataset [255,0,0] signals only a device instruction, not a specific color. This instruction [R,G,B]=[255,0,0] then causes the connected display to show Red at the maximum achievable brightness [255], while the Green and Blue components of the display remain dark [0]. The resultant color being displayed, however, depends on two main factors:

• the phosphors or another system actually producing a light that falls inside the red spectrum; • the overall brightness of the color resulting in the desired color perception: an extremely bright light source will always be seen as white, irrespective of spectral composition.

Hence every output device will have its unique color signature, displaying a certain color according to manufacturing tolerances and material deterioration through use and age. If the output device is a printer, additional distorting factors are the qualities of a particular batch of paper and ink.

79 80 CHAPTER 6. DAY 6

The conductive qualities and standards-compliance of connecting cables, circuitry and equipment can also alter the electrical signal at any stage in the signal ﬂow. (A partially inserted VGA connector can result in a monochrome display, for example, as some pins are not connected.)

6.1.2 Color perception

Color perception is subject to ambient light levels, and the ambient white point; for example, a red object looks black in blue light. It is therefore not possible to achieve calibration that will make a device look correct and consistent in all capture or viewing conditions. The computer display and calibration target will have to be considered in controlled, predeﬁned lighting conditions.

6.1.3 Calibration techniques and procedures

Calibration Target of the "Mars Hand Lens Imager (MAHLI)" on the Mars Curiosity rover (September 9, 2012) (3-D image).

The most common form of calibration aims at adjusting cameras, scanners, monitors and printers for photographic reproduction. The aim is that a printed copy of a photograph appear identical in saturation and dynamic range to the original or a source ﬁle on a computer display. This means that three independent calibrations need to be performed:

• The camera or scanner needs a device-speciﬁc calibration to represent the original’s estimated colors in an unambiguous way. 6.1. COLOR CALIBRATION 81

• The computer display needs a device-speciﬁc calibration to reproduce the colors of the image color space.

• The printer needs a device-speciﬁc calibration to reproduce the colors of the image color space.

These goals can either be realized via direct value translation from source to target, or by using a common known reference color space as middle ground. In the most commonly used color proﬁle system, ICC, this is known as the PCS or “Proﬁle Connection Space”.

Camera

The camera calibration needs a known calibration target to be photographed and the resulting output from the camera to be converted to color values. A correction proﬁle can then be built using the diﬀerence between the camera result values and the known reference values. When two or more cameras need to be calibrated relatively to each other, to reproduce the same color values, the technique of color mapping can be used.

Scanner

An IT8.7 Target by LaserSoft Imaging

For creating a scanner profile it needs a target source, such as an IT8-target, an original with many small color fields, which was measured by the developer with a photometer. The scanner reads this original and compares the scanned color values with the target’s reference values. Taking the differences of these values into account an ICC profile is created, which relates the device specific color space (RGB color space) to a device independent color space (L*a*b* color space). Thus, the scanner is able to output with color fidelity to what it reads. 82 CHAPTER 6. DAY 6

Color calibration of a laptop using Spyder4Elite colorimeter placed on the screen

Display

For calibrating the monitor a colorimeter is attached flat to the display’s surface, shielded from all ambient light. The calibration software sends a series of color signals to the display and compares the values that were actually sent against the readings from the calibration device. This establishes the current offsets in color display. Depending on the calibration software and type of monitor used, the software either creates a correction matrix (i.e. an ICC profile) for color values before being sent to the display, or gives instructions for altering the display’s brightness/contrast and RGB values through the OSD. This tunes the display to reproduce fairly accurately the in-gamut part of a desired color space. The calibration target for this kind of calibration is that of print stock paper illuminated by D65 light at 120 cd/m2.

Printer

The ICC profile for a printer is created by comparing a test print result using a photometer with the original reference file. The testchart contains known CMYK colors, whose offsets to their actual L*a*b* colors scanned by the photometer are resulting in an ICC profile. Another possibility to ICC profile a printer is to use a calibrated scanner as the measuring device for the printed CMYK testchart instead of a photometer. A calibration profile is necessary for each printer/paper/ink combination.

6.1.4 See also

• List of colors • Color chart • Color management • Color mapping • ICC proﬁle • IT8 6.2. INTERNATIONAL COLOR CONSORTIUM 83

6.1.5 References

[1] Graeme Gill. “Calibration vs. Characterization”. Graeme Gill.

[2] Hsien-Che Lee (2005). Introduction to color imaging science. Cambridge University Press. ISBN 0-521-84388-X.

[3] Ann L. McCarthy. “Color Imaging Workﬂow Primitives” (PDF). International Color Consortium.

6.1.6 External links

• monitorsetup.com Free website for checking the monitor calibration and the color management capabilities of web browsers

• CoCa - www.dohm.com.au/coca/index.html Color Camera Calibrator - an open source scanner and digital camera color calibration (ICC proﬁling) software by Andrew Stawowczyk Long

• DryCreekPhoto - Science and Information of Color calibration.

6.2 International Color Consortium

The International Color Consortium was formed in 1993 by eight vendors in order to create an open, vendor-neutral color management system which would function transparently across all operating systems and software packages. The ICC specification, currently on version 4.3,[1] allows for matching of color when moved between applications and operating systems, from the point of creation to the final output, whether display or print. This specification is technically identical to ISO 15076-1:2010, available from ISO. The ICC profile which describe the color attributes of a particular device or viewing requirement by defining a mapping between the source or target color space and a profile connection space (PCS). The ICC defines the format precisely but does not define algorithms or processing details. This means there is room for variation between different applications and systems that work with ICC profiles. ICC has also published a preliminary specification for iccMAX, a next-generation color management architecture with significantly expanded functionality and a choice of colorimetric, spectral or material connection space. Details are at http://www.color.org/iccmax/

6.2.1 ICC proﬁle speciﬁcation version

6.2.2 Membership

The eight founding members of the ICC were Adobe, Agfa, Apple, Kodak, Microsoft, Silicon Graphics, Sun Mi- crosystems, and Taligent. Since then Sun Microsystems, Silicon Graphics, and Taligent have left the organization, and many other ﬁrms have become ICC members, including, as of January 2011, Canon, Fuji, Fujitsu, Heidelberg Printing Machines AG, Hewlett–Packard, Konica Minolta, Kyocera, Lexmark, NEC, Nikon, Nokia, OKI Data, Sun Chemical, Heidelberger Druckmaschinen, and X-Rite.[2] At the beginning of 2014, ICC membership has grown to a total of 61 members, including their founding, regular, and honorary members. Aside from members of the photography, printing, and painting industry, new members from several diﬀerent industries include MathWorks, Nokia, Sony Corporation, and Signazon.com.[3]

6.2.3 See also

• International Colour Association

• International Commission on Illumination 84 CHAPTER 6. DAY 6

6.2.4 References

[1] Speciﬁcation ICC.1:2010-12 , 2010 revision of the ICC proﬁle standard

[2] ICC Members

[3] ICC Members

6.2.5 External links

• Oﬃcial Web site

6.3 International Colour Association

The International Colour Association (Association Internationale de la Couleur (AIC), or Internationale Vereini- gung für die Farbe) is a learned society whose aims are to encourage research in all aspects of color, to disseminate the knowledge gained from this research, and to promote its application to the solution of problems in the ﬁelds of science, art, design and industry on an international basis. The AIC also aims for a close cooperation with existing international organizations, such as, for example, the International Commission on Illumination (CIE), the International Organization for Standardization (ISO), and the International Commission for Optics (ICO), regarding issues concerned with color.[1] The AIC will neither duplicate the work of these bodies nor will it attempt to assume any of their responsibilities. In 2009 the AIC agreed on the creation of an International Colour Day, which is celebrated in many countries around the world.

6.3.1 History

The AIC foundation occurred on 21 June 1967 in Washington DC, USA, during the 16th Session of the CIE (Com- mission Internationale de l’Éclairage).[2] Its presidents have been, in chronological order:

• William David Wright (1967-1969, Great Britain),

• Yves LeGrand (1970-1973, France),

• Tarow Indow (1974-1977, Japan),

• C. James Bartleson (1978-1981, USA),

• Robert William G. Hunt (1982-1985, Great Britain),

• Heinz Terstiege (1986-1989, Germany), 6.3. INTERNATIONAL COLOUR ASSOCIATION 85

• Alan R. Robertson (1990-1993, Canada),

• Lucia R. Ronchi (1994-1997, Italy),

• Mitsuo Ikeda (1998-2001, Japan),

• Paula J. Alessi (2002-2005, USA),

• José Luis Caivano (2006-2009, Argentina),

• Berit Bergström (2010-2013, Sweden),

• Javier Romero (2014-2015, Spain).

6.3.2 Congresses

Every four years, the AIC organizes international color congresses. It is also responsible for arranging midterm meetings, which take place two years after the congress, and interim meetings, which take place at intervals corresponding to one and three years after the congress. Congresses feature original papers in all themes and ﬁelds related to color. Interim and Midterm Meetings, instead, are thematically oriented; each meeting concentrates on a speciﬁc aspect of color. The papers presented at congresses and meetings are published in the proceedings, most of which are freely available at http://www.aic-color.org/congr.htm.

6.3.3 Members and Executive Committee

The regular members of the AIC are color associations of diﬀerent countries or regions. In addition, it has individual members (persons), and associate members (other related international societies). The executive committee of the AIC is made of seven persons: a president, a vice president, a secretary/treasurer, and four ordinary members. This committee, whose seven members must belong to diﬀerent countries, is renewed every two years by means of elections that take place at the assemblies held during full congresses and midterm meetings.

6.3.4 Deane B. Judd Award

Since 1975, every two years, the AIC gives an international prize to individual researchers or small groups of researchers to recognize outstanding work in the ﬁeld of color science: the Deane B. Judd Award. The selection is an arduous procedure that includes nominations by AIC members and analysis of antecedents of the nominees by a committee composed of previous recipients of the award. The color researchers that have received this award are:

• 1975: Dorothy Nickerson (USA);

• 1977: William David Wright (Great Britain);

• 1979: Gunter Wyszecki (Germany, USA, Canada);

• 1981: Manfred Richter (Germany);

• 1983: David MacAdam (USA);

• 1985: Leo Hurvich and Dorothea Jameson (USA);

• 1987: Robert William G. Hunt (Great Britain);

• 1989: Tarow Indow (Japan, USA);

• 1991: Johannes J. Vos and Pieter L. Walraven (The Netherlands);

• 1993: Yoshinobu Nayatani (Japan);

• 1995: Heinz Terstiege (Germany);

• 1997: Anders Hård, Gunnar Tonnquist and Lars Sivik (Sweden); 86 CHAPTER 6. DAY 6

• 1999: Fred W. Billmeyer Jr. (USA);

• 2001: Roberto Daniel Lozano (Argentina); • 2003: Mitsuo Ikeda (Japan);

• 2005: John B. Hutchings (Great Britain); • 2007: Alan R. Robertson (Canada);

• 2009: Arne Valberg (Norway); • 2011: Lucia Ronchi (Italy);

• 2013: Roy S. Berns (USA).

6.3.5 References

[1] Gunnar Tonnquist. “25 years of colour with the AIC --and 25 000 without”. Color Research and Application 18 (5), 1993, 353-365.

[2] Gunnar Tonnquist. “The early history of the Association Internationale de la Couleur (AIC)". In AIC Color 77, Proceedings of the Third Congress, Troy, New York, 10–15 July (Bristol, England: Adam Hilger, 1978), 13-32. http://www.aic-color. org/Tonnquist77.pdf

6.3.6 External links

• www.aic-color.org Chapter 7

Day 7

7.1 Lab color space

A Lab color space is a color-opponent space with dimensions L for lightness and a and b for the color-opponent dimensions, based on nonlinearly compressed (e.g. CIE XYZ) coordinates. The terminology originates from the three dimensions of the Hunter 1948 color space, which are L, a, and b.[1][2] However, nowadays Lab is usually an informal abbreviation for the L*a*b* representation of the CIE 1976 color space (or CIELAB, described below), where the asterisks/stars are used to distinguish the CIE version from Hunter’s original version. The difference between the original Hunter and CIE color coordinates is that the CIE coordinates are based on a cube root transformation of the color data, while the Hunter coordinates are based on a square root transformation. Other examples of color spaces with Lab representations include the CIE 1994 color space and the CIE 2000 color space. The L*a*b* color space includes all perceivable colors, which means that its gamut exceeds those of the RGB and CMYK color models (for example, ProPhoto RGB includes about 90% all perceivable colors). One of the most important attributes of the L*a*b*-model is device independence. This means that the colors are defined independent of their nature of creation or the device they are displayed on. The L*a*b* color space is used when graphics for print have to be converted from RGB to CMYK, as the L*a*b* gamut includes both the RGB and CMYK gamut. Also it is used as an interchange format between different devices as for its device independency. The space itself is a three-dimensional real number space, that contains an infinite number of possible representations of colors. However, in practice, the space is usually mapped onto a three-dimensional integer space for device-independent digital representation, and for these reasons, the L*, a*, and b* values are usually absolute, with a pre-defined range. The lightness, L*, represents the darkest black at L* = 0, and the brightest white at L* = 100. The color channels, a* and b*, will represent true neutral gray values at a* = 0 and b* = 0. The red/green opponent colors are represented along the a* axis, with green at negative a* values and red at positive a* values. The yellow/blue opponent colors are represented along the b* axis, with blue at negative b* values and yellow at positive b* values. The scaling and limits of the a* and b* axes will depend on the specific implementation of Lab color, as described below, but they often run in the range of ±100 or −128 to +127 (signed 8-bit integer). Both the Hunter and the 1976 CIELAB color spaces were derived from the prior “master” space CIE 1931 XYZ color space, which can predict which spectral power distributions will be perceived as the same color (see metamerism), but which is not particularly perceptually uniform.[3] Strongly influenced by the Munsell color system, the intention of both “Lab” color spaces is to create a space that can be computed via simple formulas from the XYZ space but is more perceptually uniform than XYZ.[4] Perceptually uniform means that a change of the same amount in a color value should produce a change of about the same visual importance. When storing colors in limited precision values, this can improve the reproduction of tones. Both Lab spaces are relative to the white point of the XYZ data they were converted from. Lab values do not define absolute colors unless the white point is also specified. Often, in practice, the white point is assumed to follow a standard and is not explicitly stated (e.g., for “absolute colorimetric” rendering intent, the International Color Consortium L*a*b* values are relative to CIE standard illuminant D50, while they are relative to the unprinted substrate for other rendering intents).[5] The lightness correlate in CIELAB is calculated using the cube root of the relative luminance.

87 88 CHAPTER 7. DAY 7

7.1.1 Advantages

Unlike the RGB and CMYK color models, Lab color is designed to approximate human vision. It aspires to perceptual uniformity, and its L component closely matches human perception of lightness, although it does not take the Helmholtz–Kohlrausch eﬀect into account. Thus, it can be used to make accurate color balance corrections by modifying output curves in the a and b components, or to adjust the lightness contrast using the L component. In RGB or CMYK spaces, which model the output of physical devices rather than human visual perception, these transformations can be done only with the help of appropriate blend modes in the editing application. Because Lab space is much larger than the gamut of computer displays, printers, or even human vision, a bitmap image represented as Lab requires more data per pixel to obtain the same precision as an RGB or CMYK bitmap. In the 1990s, when computer hardware and software were limited to storing and manipulating mostly 8-bit/channel bitmaps, converting an RGB image to Lab and back was a very lossy operation. With 16-bit/channel and ﬂoating-point support now common, the loss due to quantization is negligible. In addition, many of the “colors” within Lab space fall outside the gamut of human vision, and are therefore purely imaginary; these “colors” cannot be reproduced in the physical world. Though color management software, such as that built into image editing applications, will pick the closest in-gamut approximation, changing lightness, chroma, and sometimes hue in the process, author Dan Margulis claims that this access to imaginary colors is useful, going between several steps in the manipulation of a picture.[6]

7.1.2 Diﬀerentiation

Some speciﬁc uses of the abbreviation in software, literature etc.

• In Adobe Photoshop, image editing using “Lab mode” is CIELAB D50.[6][7] • In ICC profiles, the “Lab color space” used as a profile connection space is CIELAB D50.[5] • In TIFF files, the CIELAB color space may be used.[8] • In PDF documents, the “Lab color space” is CIELAB.[9][10] • In Digital Color Meter on OS X, it is described as “L*a*b*" • In the open source non-destructive-editing software RawTherapee, an entire tab with many controls is dedicated to the CIE Color Appearance Model

7.1.3 CIELAB

CIE L*a*b* (CIELAB) is a color space specified by the International Commission on Illumination (French Com- mission internationale de l'éclairage, hence its CIE initialism). It describes all the colors visible to the human eye and was created to serve as a device-independent model to be used as a reference. The three coordinates of CIELAB represent the lightness of the color (L* = 0 yields black and L* = 100 indicates diffuse white; specular white may be higher), its position between red/magenta and green (a*, negative values indicate green while positive values indicate magenta) and its position between yellow and blue (b*, negative values indicate blue and positive values indicate yellow). The asterisk (*) after L, a and b are pronounced star and are part of the full name, since they represent L*, a* and b*, to distinguish them from Hunter’s L, a, and b, described below. Since the L*a*b* model is a three-dimensional model, it can be represented properly only in a three-dimensional space.[11] Two-dimensional depictions include chromaticity diagrams: sections of the color solid with a fixed lightness. It is crucial to realize that the visual representations of the full gamut of colors in this model are never accurate; they are there just to help in understanding the concept. Because the red-green and yellow-blue opponent channels are computed as differences of lightness transformations of (putative) cone responses, CIELAB is a chromatic value color space. A related color space, the CIE 1976 (L*, u*, v*) color space (a.k.a. CIELUV), preserves the same L* as L*a*b* but has a different representation of the chromaticity components. CIELAB and CIELUV can also be expressed in cylindrical form (CIELCH[12] and CIELCHᵤᵥ, respectively), with the chromaticity components replaced by correlates of chroma and hue. 7.1. LAB COLOR SPACE 89

Since CIELAB and CIELUV, the CIE has been incorporating an increasing number of color appearance phenomena into their models, to better model color vision. These color appearance models, of which CIELAB is a simple example,[13] culminated with CIECAM02.

Perceptual diﬀerences

This topic is covered in more detail at Color diﬀerence. The nonlinear relations for L*, a*, and b* are intended to mimic the nonlinear response of the eye. Furthermore, uniform changes of components in the L*a*b* color space aim to correspond to uniform changes in perceived color, so the relative perceptual diﬀerences between any two colors in L*a*b* can be approximated by treating each color as a point in a three-dimensional space (with three components: L*, a*, b*) and taking the Euclidean distance between them.[14]

RGB and CMYK conversions

There are no simple formulas for conversion between RGB or CMYK values and L*a*b*, because the RGB and CMYK color models are device-dependent. The RGB or CMYK values ﬁrst must be transformed to a speciﬁc absolute color space, such as sRGB or Adobe RGB. This adjustment will be device-dependent, but the resulting data from the transform will be device-independent, allowing data to be transformed to the CIE 1931 color space and then transformed into L*a*b*.

Range of coordinates

As mentioned previously, the L* coordinate ranges from 0 to 100. The possible range of a* and b* coordinates is independent of the color space that one is converting from, since the conversion below uses X and Y, which come from RGB.

7.1.4 CIELAB-CIEXYZ conversions

Forward transformation ( ) Y 1/3 L⋆ = 116 − 16 Y0 (( ) ( ))1/3 X 1/3 Y a⋆ = 500 − X0 Y0 (( ) ( ))1/3 Y 1/3 Z b⋆ = 200 − Y0 Z0 where

{√ 3 t ift > δ3 f(t) = t 4 3δ2 + 29 otherwise 6 δ = 29 Here, X, Y and Z are the CIE XYZ tristimulus values of the reference white point (the subscript n suggests “normalized”). Under Illuminant D65 with normalization Y = 100, the values are

Xn = 95.047,

Yn = 100.000,

Zn = 108.883 90 CHAPTER 7. DAY 7

The division of the domain of the f function into two parts was done to prevent an inﬁnite slope at t = 0. The function 1/3 f was assumed to be linear below some t = t0, and was assumed to match the t part of the function at t0 in both value and slope. In other words:

1/3 t0 = mt0 + c value) in (match 1 − t 2/3 = m slope) in (match 3 0 The intercept f(0) = c was chosen so that L* would be 0 for Y = 0: c = 16/116 = 4/29. The above two equations can be solved for m and t0:

1 m = δ−2 = 7.787037 ... 3 3 t0 = δ = 0.008856 ... where δ = 6/29.[15]

Reverse transformation

The reverse transformation is most easily expressed using the inverse of the function f above:

( ) L⋆ + 16 a⋆ X = X f −1 + n 116 500 ( ) L⋆ + 16 Y = Y f −1 n 116 ( ) L⋆ + 16 b⋆ Z = Z f −1 − n 116 200 where

{ t3 ift > δ f −1(t) = ( ) 2 − 4 3δ t 29 otherwise and where δ = 6/29.

7.1.5 Hunter Lab

L is a correlate of lightness, and is computed from the Y tristimulus value using Priest’s approximation to Munsell value:

√ L = 100 Y /Yn where Y is the Y tristimulus value of a specified white object. For surface-color applications, the specified white object is usually (though not always) a hypothetical material with unit reflectance that follows Lambert’s law. The resulting L will be scaled between 0 (black) and 100 (white);√ roughly ten times the Munsell value. Note that a medium lightness of 50 is produced by a luminance of 25, since 100 25/100 = 100 · 1/2 a and b are termed opponent color axes. a represents, roughly, Redness (positive) versus Greenness (negative). It is computed as:

( ) X/Xn − Y /Yn a = Ka √ Y /Yn 7.1. LAB COLOR SPACE 91

where Kₐ is a coeﬃcient that depends upon the illuminant (for D65, Kₐ is 172.30; see approximate formula below) and X is the X tristimulus value of the speciﬁed white object. The other opponent color axis, b, is positive for yellow colors and negative for blue colors. It is computed as:

( ) Y /Yn − Z/Zn b = Kb √ Y /Yn where K is a coefficient that depends upon the illuminant (for D65, K is 67.20; see approximate formula below) and Z is the Z tristimulus value of the specified white object.[16] Both a and b will be zero for objects that have the same chromaticity coordinates as the specified white objects (i.e., achromatic, grey, objects). The name for the system is an attribution to Richard S. Hunter.

Approximate formulas for Kₐ and K

In the previous version of the Hunter Lab color space, Kₐ was 175 and K was 70. Hunter Associates Lab discovered that better agreement could be obtained with other color diﬀerence metrics, such as CIELAB (see above) by allowing these coeﬃcients to depend upon the illuminants. Approximate formulae are:

175 K ≈ (X + Y ) a 198.04 n n 70 K ≈ (Y + Z ) b 218.11 n n which result in the original values for Illuminant C, the original illuminant with which the Lab color space was used.

As an Adams chromatic valence space

Adams chromatic valence color spaces are based on two elements: a (relatively) uniform lightness scale, and a (relatively) uniform chromaticity scale.[17] If we take as the uniform lightness scale Priest’s approximation to the Munsell Value scale, which would be written in modern notation:

√ L = 100 Y /Yn and, as the uniform chromaticity coordinates:

X/Xn X/Xn − Y /Yn ca = − 1 = Y /Yn Y /Yn ( ) Z/Zn Y /Yn − Z/Zn cb = ke 1 − = ke Y /Yn Y /Yn where kₑ is a tuning coeﬃcient, we obtain the two chromatic axes:

X/Xn − Y /Yn a = K · L · ca = K · 100 √ Y /Yn and

Y /Yn − Z/Zn b = K · L · cb = K · 100ke √ Y /Yn which is identical to the Hunter Lab formulas given above if we select K = Kₐ/100 and kₑ = K/Kₐ. Therefore, the Hunter Lab color space is an Adams chromatic valence color space. 92 CHAPTER 7. DAY 7

7.1.6 Cylindrical representation: CIELCh or CIEHLC

The CIELCh color space is a CIELab cube color space, where instead of Cartesian coordinates a*, b*, the cylindrical coordinates C* (chroma, relative saturation) and h° (hue angle, angle of the hue in the CIELab color wheel) are speciﬁed. The CIELab lightness L* remains unchanged. The conversion of a* and b* to C* and h° is done using the following formulas:

√ ( ) b⋆ C⋆ = a⋆ 2 + b⋆ 2, h◦ = arctan a⋆

Conversely, given the polar coordinates, conversion to Cartesian coordinates is achieved with:

a⋆ = C⋆ cos(h◦), b⋆ = C⋆ sin(h◦)

The LCh color space is not the same as the HSV, HSL or HSB color spaces, although their values can also be interpreted as a base color, saturation and lightness of a color. The LCh values are a polar coordinate transformation of what is technically defined RGB cube color space. LCh is still perceptually uniform. Further, H and h are not identical, because HSL space uses as primary colors the three additive primary colors red, green, blue (H = 0, 120, 240°). Instead, the LCh system uses the four physiological elementary colors yellow, green, blue and red (h = 90, 180, 270, 360°). h = 0 means the achromatic colors, that is, the gray axis. The simplified spellings LCh, LCH and HLC are common, but the latter presents a different order. HCL color space (Hue-Chroma-Luminance) on the other hand is a commonly used alternative name for the L*C*h(uv) color space, also known as the cylindrical representation or polar CIELUV.

7.1.7 See also

• Color theory

• HSL and HSV

• RGB color model

• CMYK color model

• CIECAM02

• HCL color space

7.1.8 References

[1] Hunter, Richard Sewall (July 1948). “Photoelectric Color-Diﬀerence Meter”. JOSA. 38 (7): 661. (Proceedings of the Winter Meeting of the Optical Society of America)

[2] Hunter, Richard Sewall (December 1948). “Accuracy, Precision, and Stability of New Photo-electric Color-Diﬀerence Meter”. JOSA. 38 (12): 1094. (Proceedings of the Thirty-Third Annual Meeting of the Optical Society of America)

[3] A discussion and proposed improvement, Bruce Lindbloom

[4] Explanation of this history, Bruce MacEvoy

[5] International Color Consortium, Specification ICC.1:2004-10 (Profile version 4.2.0.0) Image technology colour management — Architecture, profile format, and data structure, (2006).

[6] Margulis, Dan (2006). Photoshop Lab Color: The Canyon Conundrum and Other Adventures in the Most Powerful Col- orspace. Berkeley, Calif. : London: Peachpit ; Pearson Education. ISBN 0-321-35678-0.

[7] The Lab Color Mode in Photoshop, Adobe TechNote 310838

[8] TIFF: Revision 6.0 Adobe Developers Association, 1992 7.1. LAB COLOR SPACE 93

[9] Color Consistency and Adobe Creative Suite

[10] Adobe Acrobat Reader 4.0 User Guide “The color model Acrobat Reader uses is called CIELAB…"

[11] 3D representations of the L*a*b* gamut, Bruce Lindbloom.

[12] CIE-L*C*h Color Scale

[13] Fairchild, Mark D. (2005). “Color and Image Appearance Models”. Color Appearance Models. John Wiley and Sons. p. 340. ISBN 0-470-01216-1.

[14] Jain, Anil K. (1989). Fundamentals of Digital Image Processing. New Jersey, United States of America: Prentice Hall. pp. 68, 71, 73. ISBN 0-13-336165-9.

[15] János Schanda (2007). Colorimetry. Wiley-Interscience. p. 61. ISBN 978-0-470-04904-4.

[16] Hunter Labs (1996). “Hunter Lab Color Scale”. Insight on Color 8 9 (August 1–15, 1996). Reston, VA, USA: Hunter Associates Laboratories.

[17] Adams, E.Q. (1942). “X-Z planes in the 1931 I.C.I. system of colorimetry”. JOSA. 32 (3): 168–173. doi:10.1364/JOSA.32.000168.

7.1.9 External links

• Demonstrative color conversion applet • CIELAB Color Space by Gernot Hoﬀmann, includes explanations of L*a*b* conversion formulae, graphical depictions of various gamuts plotted in L*a*b* space, and PostScript code for performing the color transformations.

• Color Diﬀerences • LAB Color Spaces with MATLAB 94 CHAPTER 7. DAY 7

The CIE 1976 (L*, a*, b*) color space (CIELAB), showing only colors that ﬁt within the sRGB gamut (and can therefore be displayed on a typical computer display). Each axis of each square ranges from −128 to 128. 7.1. LAB COLOR SPACE 95

An example of color enhancement using LAB colorspace in Photoshop. The left side of the photo is enhanced, while the right side is normal. 96 CHAPTER 7. DAY 7

The sRGB gamut plotted within the CIELAB color space. L is the vertical axis; a and b are the horizontal axes. 7.1. LAB COLOR SPACE 97

The sRGB gamut plotted within the cylindrical CIE LChab color space. L is the vertical axis; C is the cylinder radius; h is the angle around the circumference. 98 CHAPTER 7. DAY 7

7.2 sRGB

CIE 1931 xy chromaticity diagram showing the gamut of the sRGB color space and location of the primaries. The D65 white point is shown in the center. The Planckian locus is shown with color temperatures labeled in kelvin. The outer curved boundary is the spectral (or monochromatic) locus, with wavelengths shown in nanometers (labeled in blue). Note that the colors in this displayed file are being specified using sRGB. Areas outside the triangle cannot be accurately colored because they are out of the gamut of sRGB therefore they have been interpreted. Also note how the D65 label is not an ideal 6500-kelvin blackbody because it is based on atmospheric filtered daylight. sRGB is a standard RGB color space created cooperatively by HP and Microsoft in 1996 for use on monitors, printers and the Internet, and subsequently standardized by the IEC as IEC 61966-2-1:1999.[1] sRGB uses the ITU-R BT.709 primaries, the same as are used in studio monitors and HDTV,[2] and a transfer function (gamma curve) typical of CRTs. This specification allowed sRGB to be directly displayed on typical CRT monitors of the time, a factor which greatly aided its acceptance. 7.2. SRGB 99

7.2.1 Background

The sRGB color space has been endorsed by the W3C, Exif, Intel, Pantone, Corel, and many other industry players. It is used in proprietary and open graphics file formats, such as SVG. The sRGB color space is well specified and is designed to match typical home and office viewing conditions, rather than the darker environment typically used for commercial color matching. Much software is now designed with the assumption that an 8-bit-per-channel image placed unchanged onto an 8-bit- per-channel display will appear much as the sRGB specification recommends. LCDs, digital cameras, printers, and scanners all follow the sRGB standard. Devices which do not naturally follow sRGB (such as older CRT monitors) include compensating circuitry or software so that, in the end, they also obey this standard. For this reason, one can generally assume, in the absence of embedded profiles or any other information, that any 8-bit-per-channel image file or any 8-bit-per-channel image API or device interface can be treated as being in the sRGB color space. However, when the correct displaying of an RGB color space is needed, color management usually must be employed.

7.2.2 The sRGB gamut sRGB deﬁnes the chromaticities of the red, green, and blue primaries, the colors where one of the three channels is nonzero and the other two are zero. The gamut of chromaticities that can be represented in sRGB is the color triangle deﬁned by these primaries. As with any RGB color space, for non-negative values of R, G, and B it is not possible to represent colors outside this triangle, which is well inside the range of colors visible to a human with normal trichromatic vision. sRGB is sometimes avoided by high-end print publishing professionals because its color gamut is not big enough, especially in the blue-green colors, to include all the colors that can be reproduced in CMYK printing.

7.2.3 The sRGB transfer (gamma) function sRGB also defines a nonlinear transformation between the intensity of these primaries and the actual number stored. The curve is similar to the gamma response of a CRT display. It is more important to replicate this curve than the primaries to get correct display of an sRGB image. This nonlinear conversion means that sRGB is a reasonably efficient use of the values in an integer-based image file to display human-discernible light levels. Unlike most other RGB color spaces, the sRGB gamma cannot be expressed as a single numerical value. The overall gamma is approximately 2.2, consisting of a linear (gamma 1.0) section near black, and a non-linear section elsewhere involving a 2.4 exponent and a gamma (slope of log output versus log input) changing from 1.0 through about 2.3. The purpose of the linear section is so the curve does not have an infinite slope at zero, it is not for matching CRT behavior.

7.2.4 Speciﬁcation of the transformation

The forward transformation (CIE XYZ to sRGB)

The CIE XYZ values must be scaled so that the Y of D65(“white”) is 1.0 (X,Y,Z = 0.9505, 1.0000, 1.0890). This is usually true but some color spaces use 100 or other values (such as in the Lab article). The first step in the calculation of sRGB from CIE XYZ is a linear transformation, which may be carried out by a matrix multiplication. (The numerical values below match those in the official sRGB specification[1] which corrected some small rounding errors in the original publication[3] by sRGB’s creators, and assume the 2° standard colorimetric observer for CIE XYZ[3])

     Rlinear 3.2406 −1.5372 −0.4986 X      Glinear = −0.9689 1.8758 0.0415 Y Blinear 0.0557 −0.2040 1.0570 Z

It is important to note that these linear RGB values are not the ﬁnal result as they have not been adjusted for the gamma correction. sRGB was designed to reﬂect a typical real-world monitor with a gamma of 2.2, and the 100 CHAPTER 7. DAY 7

2 1

1.5

1 0.5

0.5

0 0 0 0.2 0.4 0.6 0.8 1

Plot of the sRGB intensities versus sRGB numerical values (red), and this function’s slope in log-log space (blue) which is the eﬀective gamma at each point. Below a compressed value of 0.04045 or a linear intensity of 0.00313, the curve is linear so the gamma is 1. Behind the red curve is a dashed black curve showing an exact gamma = 2.2 power law.

On an sRGB display, each solid bar should look as bright as the surrounding striped dither. (Note: must be viewed at original, 100% size)

following formula transforms the linear RGB values into sRGB. Let Clinear be Rlinear , Glinear , or Blinear , and Csrgb be Rsrgb , Gsrgb or Bsrgb : 7.2. SRGB 101

{ 12.92C , C ≤ 0.0031308 C = linear linear srgb 1/2.4 − (1 + a)Clinear a, Clinear > 0.0031308

• where a = 0.055

These gamma-corrected values are in the range 0 to 1. If values in the range 0 to 255 are required, e.g. for video display or 8-bit graphics, the usual technique is to multiply by 255 and round to an integer. The values are usually clipped to the 0 to 1 range. This clipping can be done before or after this gamma calculation, or done as part of converting to 8 bits.

The reverse transformation

Again the sRGB component values Rsrgb , Gsrgb , Bsrgb are in the range 0 to 1. (A range of 0 to 255 can simply be divided by 255).

  Csrgb , C ≤ 0.04045 (12.92 ) srgb Clinear = 2.4  Csrgb+a 1+a ,Csrgb > 0.04045

• where a = 0.055 and where C is R , G , or B .

Followed by a matrix multiplication of the linear values to get XYZ:

     X 0.4124 0.3576 0.1805 Rlinear      Y = 0.2126 0.7152 0.0722 Glinear Z 0.0193 0.1192 0.9505 Blinear

7.2.5 Theory of the transformation

It is often casually stated that the decoding gamma for sRGB data is 2.2, yet the above transform shows an exponent of 2.4. This is because the net effect of the piecewise decomposition is necessarily a changing instantaneous gamma at each point in the range: it goes from gamma = 1 at zero to a gamma of 2.4 at maximum intensity with a median value being close to 2.2. The transformation was designed to approximate a gamma of about 2.2, but with a linear portion near zero to avoid having an infinite slope at K = 0, which can cause numerical problems. The continuity condition for the curve Clinear which is defined above as a piecewise function of Csrgb , is

( ) K + a γ K 0 = 0 . 1 + a ϕ

Solving with γ = 2.4 and the standard value ϕ = 12.92 yields two solutions, K0 ≈ 0.0381548 or K0 ≈ 0.0404482 . The IEC 61966-2-1 standard uses the rounded value K0 = 0.04045 . However, if we impose the condition that the slopes match as well then we must have

( ) − ( ) K + a γ 1 1 1 γ 0 = . 1 + a 1 + a ϕ

We now have two equations. If we take the two unknowns to be K0 and ϕ then we can solve to give

a (1 + a)γ (γ − 1)γ−1 K = , ϕ = . 0 γ − 1 (aγ−1)(γγ ) 102 CHAPTER 7. DAY 7

Substituting a = 0.055 and γ = 2.4 gives K0 ≈ 0.0392857 and ϕ ≈ 12.9232102 , with the corresponding linear- domain threshold at K0/ϕ ≈ 0.00303993 . These values, rounded to K0 = 0.03928 , ϕ = 12.92321 , and K0/ϕ = [4] [3] 0.00304 , are sometimes used to describe sRGB conversion. Publications by sRGB’s creators rounded to K0 = 0.03928 and ϕ = 12.92 , resulting in a small discontinuity in the curve. Some authors adopted these values in spite [5] of the discontinuity. For the standard, the rounded value ϕ = 12.92 was kept and the K0 value was recomputed to make the resulting curve continuous, as described above, resulting in a slope discontinuity from 12.92 below the intersection to 12.70 above.

7.2.6 Viewing environment

The sRGB specification assumes a dimly lit encoding (creation) environment with an ambient correlated color temperature (CCT) of 5000 K. It is interesting to note that this differs from the CCT of the illuminant (D65). Using D50 for both would have made the white point of most photographic paper appear excessively blue.[6] The other parameters, such as the luminance level, are representative of a typical CRT monitor. For optimal results, the ICC recommends using the encoding viewing environment (i.e., dim, diffuse lighting) rather than the less-stringent typical viewing environment.[3]

7.2.7 Usage

Due to the standardization of sRGB on the Internet, on computers, and on printers, many low- to medium-end consumer digital cameras and scanners use sRGB as the default (or only available) working color space. As the sRGB gamut meets or exceeds the gamut of a low-end inkjet printer, an sRGB image is often regarded as satisfactory for home use. However, consumer-level CCDs are typically uncalibrated, meaning that even though the image is being labeled as sRGB, one can't conclude that the image is color-accurate sRGB. If the color space of an image is unknown and it is an 8- to 16-bit image format, assuming it is in the sRGB color space is a safe choice. This allows a program to identify a color space for all images, which may be much easier and more reliable than trying to track the “unknown” color space. An ICC profile may be used; the ICC distributes three such profiles:[7] a profile conforming to version 4 of the ICC specification, which they recommend, and two profiles conforming to version 2, which is still commonly used. Images intended for professional printing via a fully color-managed workflow, e.g. prepress output, sometimes use another color space such as Adobe RGB (1998), which allows for a wider gamut. If such images are to be used on the Internet they may be converted to sRGB using color management tools that are usually included with software that works in these other color spaces. The two dominant programming interfaces for 3D graphics, OpenGL and Direct3D, have both incorporated support for the sRGB gamma curve. OpenGL supports textures with sRGB gamma encoded color components (first introduced with EXT_texture_sRGB extension, added to the core in OpenGL 2.1) and rendering into sRGB gamma encoded framebuffers (first introduced with EXT_framebuffer_sRGB extension, added to the core in OpenGL 3.0). Direct3D supports sRGB gamma textures and rendering into sRGB gamma surfaces starting with DirectX 9. Correct mipmapping and interpolation of sRGB gamma textures has direct hardware support in texturing units of most modern GPUs (for example nVidia GeForce 8 performs conversion from 8-bit texture to linear values before interpolating those values), and does not have any performance penalty.[8]

7.2.8 See also

• RGB color space

• scRGB

7.2.9 References

[1] https://webstore.iec.ch/publication/6169

[2] Charles A. Poynton (2003). Digital Video and HDTV: Algorithms and Interfaces. Morgan Kaufmann. ISBN 1-55860-792- 7. 7.2. SRGB 103

0.9 520 ProPhoto RGB

0.8 540 Adobe RGB 1998 0.7 560 Colormatch RGB 0.6 sRGB SWOP CMYK 500 0.5 580 y 0.4 600 D65 white point 620 0.3

0.2

480 0.1

0.0 460 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 x

Comparison of some RGB and CMYK colour gamuts on a CIE 1931 xy chromaticity diagram

[3] Michael Stokes; Matthew Anderson; Srinivasan Chandrasekar; Ricardo Motta (November 5, 1996). “A Standard Default Color Space for the Internet – sRGB, Version 1.10”.

[4] Phil Green & Lindsay W. MacDonald (2002). Colour Engineering: Achieving Device Independent Colour. John Wiley and Sons. ISBN 0-471-48688-4.

[5] Jon Y. Hardeberg (2001). Acquisition and Reproduction of Color Images: Colorimetric and Multispectral Approaches. Universal-Publishers.com. ISBN 1-58112-135-0.

[6] Rodney, Andrew (2005). Color Management for Photographers. Focal Press. p. 121. ISBN 978-0-240-80649-5. Why Calibrate Monitor to D65 When Light Booth is D50

[7] sRGB proﬁles, ICC

[8] GPU Gems 3, section 24.4.1, http://http.developer.nvidia.com/GPUGems3/gpugems3_ch24.html 104 CHAPTER 7. DAY 7

Standards

• IEC 61966-2-1:1999 is the oﬃcial speciﬁcation of sRGB. It provides viewing environment, encoding, and colorimetric details.

• Amendment A1:2003 to IEC 61966-2-1:1999 describes an analogous sYCC encoding for YCbCr color spaces, an extended-gamut RGB encoding, and a CIELAB transformation.

• sRGB on www.color.org

• The fourth working draft of IEC 61966-2-1 is available online, but is not the complete standard. It can be downloaded from www2.units.it.

7.2.10 External links

• International Color Consortium

• Archive copy of http://www.srgb.com, now unavailable, containing much information on the design, principles and use of sRGB

• A Standard Default Color Space for the Internet – sRGB at w3.org

• OpenGL extension for sRGB gamma textures at sgi.com

• Conversion matrices for RGB vs. XYZ conversion

• Will the Real sRGB Proﬁle Please Stand Up?

7.3 HSL and HSV

HSL and HSV are the two most common cylindrical-coordinate representations of points in an RGB color model. The two representations rearrange the geometry of RGB in an attempt to be more intuitive and perceptually relevant than the cartesian (cube) representation. Developed in the 1970s for computer graphics applications, HSL and HSV are used today in color pickers, in image editing software, and less commonly in image analysis and computer vision. HSL stands for hue, saturation, and lightness (or luminosity), and is also often called HLS. HSV stands for hue, saturation, and value, and is also often called HSB (B for brightness). A third model, common in computer vision applications, is HSI, for hue, saturation, and intensity. However, while typically consistent, these definitions are not standardized, and any of these abbreviations might be used for any of these three or several other related cylindrical models. (For technical definitions of these terms, see below.) In each cylinder, the angle around the central vertical axis corresponds to "hue", the distance from the axis corresponds to "saturation", and the distance along the axis corresponds to "lightness", “value” or "brightness". Note that while “hue” in HSL and HSV refers to the same attribute, their definitions of “saturation” differ dramatically. Because HSL and HSV are simple transformations of device-dependent RGB models, the physical colors they define depend on the colors of the red, green, and blue primaries of the device or of the particular RGB space, and on the gamma correction used to represent the amounts of those primaries. As a result, each unique RGB device has unique HSL and HSV absolute color spaces to accompany it (just as it has unique RGB absolute color space to accompany it), and the same numerical HSL or HSV values (just as numerical RGB values) may be displayed differently by different devices. Both of these representations are used widely in computer graphics, and one or the other of them is often more convenient than RGB, but both are also criticized for not adequately separating color-making attributes, or for their lack of perceptual uniformity. Other more computationally intensive models, such as CIELAB or CIECAM02, are said to better achieve these goals. 7.3. HSL AND HSV 105

Fig. 1. HSL (a–d) and HSV (e–h). Above (a, e): cut-away 3D models of each. Below: two-dimensional plots showing two of a model’s three parameters at once, holding the other constant: cylindrical shells (b, f) of constant saturation, in this case the outside surface of each cylinder; horizontal cross-sections (c, g) of constant HSL lightness or HSV value, in this case the slices halfway down each cylinder; and rectangular vertical cross-sections (d, h) of constant hue, in this case of hues 0° red and its complement 180° cyan.

7.3.1 Basic principle

HSL and HSV are both cylindrical geometries (fig. 2), with hue, their angular dimension, starting at the red primary at 0°, passing through the green primary at 120° and the blue primary at 240°, and then wrapping back to red at 360°. In each geometry, the central vertical axis comprises the neutral, achromatic, or gray colors, ranging from black at lightness 0 or value 0, the bottom, to white at lightness 1 or value 1, the top. In both geometries, the additive primary and secondary colors—red, yellow, green, cyan, blue and magenta—and linear mixtures between adjacent pairs of them, sometimes called pure colors, are arranged around the outside edge of the cylinder with saturation 1. These saturated colors have value 1 in HSV, while in HSL they have lightness ½. In HSV, mixing these pure colors with white—producing so-called tints—reduces saturation, while mixing them with black—producing shades—leaves saturation unchanged. In HSL, both tints and shades have full saturation, and only mixtures with both black and white—called tones—have saturation less than 1. Because these definitions of saturation—in which very dark (in both models) or very light (in HSL) near-neutral colors, for instance (bottom right in the sliced HSL cylinder) or (top right in the sliced HSL cylinder), are considered 106 CHAPTER 7. DAY 7 fully saturated—conflict with the intuitive notion of color purity, often a conic or bi-conic solid is drawn instead (fig. 3), with what this article calls chroma as its radial dimension, instead of saturation. Confusingly, such diagrams usually label this radial dimension “saturation”, blurring or erasing the distinction between saturation and chroma.[1] As described below, computing chroma is a helpful step in the derivation of each model. Because such an intermediate model—with dimensions hue, chroma, and HSV value or HSL lightness—takes the shape of a cone or bicone, HSV is often called the “hexcone model” while HSL is often called the “bi-hexcone model” (fig. 8).[2]

7.3.2 Motivation

Fig. 4. Painters long mixed colors by combining relatively bright pigments with black and white. Mixtures with white are called tints, mixtures with black are called shades, and mixtures with both are called tones. See Tints and shades.[3]

Fig. 5. This 1916 color model by German chemist Wilhelm Ostwald exempliﬁes the “mixtures with white and black” approach, organizing 24 “pure” colors into a hue circle, and colors of each hue into a triangle. The model thus takes the shape of a bicone.[4]

Fig. 7. Tektronix graphics terminals used the earliest commercial implementation of HSL, in 1979. This diagram, from a patent ﬁled in 1983, shows the bicone geometry underlying the model.[5]

Fig. 6a. The RGB gamut can be arranged in a cube. 7.3. HSL AND HSV 107

Fig. 6b. The same image, with a portion removed for clarity. See also: Color theory, RGB color model, and RGB color space

Most televisions, computer displays, and projectors produce colors by combining red, green, and blue light in varying intensities—the so-called RGB additive primary colors. The resulting mixtures in RGB color space can reproduce a wide variety of colors (called a gamut); however, the relationship between the constituent amounts of red, green, and blue light and the resulting color is unintuitive, especially for inexperienced users, and for users familiar with subtractive color mixing of paints or traditional artists’ models based on tints and shades (ﬁg. 4). Furthermore, neither additive nor subtractive color models deﬁne color relationships the same way the human eye does.[6] For example, imagine we have an RGB display whose color is controlled by three sliders ranging from 0–255, one controlling the intensity of each of the red, green, and blue primaries. If we begin with a relatively colorful orange , with sRGB values R = 217, G = 118, B = 33, and want to reduce its colorfulness by half to a less saturated orange , we would need to drag the sliders to decrease R by 31, increase G by 24, and increase B by 59, as pictured below.

In an attempt to accommodate more traditional and intuitive color mixing models, computer graphics pioneers at PARC and NYIT developed the HSV model in the mid-1970s, formally described by Alvy Ray Smith in the August 1978 issue of Computer Graphics. In the same issue, Joblove and Greenberg described the HSL model—whose dimensions they labeled hue, relative chroma, and intensity—and compared it to HSV (ﬁg. 1). Their model was based more upon how colors are organized and conceptualized in human vision in terms of other color-making attributes, such as hue, lightness, and chroma; as well as upon traditional color mixing methods—e.g., in painting—that involve mixing brightly colored pigments with black or white to achieve lighter, darker, or less colorful colors. The following year, 1979, at SIGGRAPH, Tektronix introduced graphics terminals using HSL for color designation, and the Computer Graphics Standards Committee recommended it in their annual status report (ﬁg. 7). These models were useful not only because they were more intuitive than raw RGB values, but also because the conversions to and from RGB were extremely fast to compute: they could run in real time on the hardware of the 1970s. Consequently, these models and similar ones have become ubiquitous throughout image editing and graphics software since then. Some of their uses are described below.[7][8][9][10][11][12]

7.3.3 Formal derivation

Color-making attributes

See also: Color vision

The dimensions of the HSV and HSL geometries—simple transformations of the not-perceptually-based RGB model— are not directly related to the photometric color-making attributes of the same names, as deﬁned by scientists such as the CIE or ASTM. Nonetheless, it is worth reviewing those deﬁnitions before leaping into the derivation of our models.[13][14][15]

Hue The “attribute of a visual sensation according to which an area appears to be similar to one of the perceived colors: red, yellow, green, and blue, or to a combination of two of them”. Radiance (Lₑ,Ω) The radiant power of light passing through a particular surface per unit solid angle per unit projected area, measured in SI units in watt per steradian per square metre (W·sr−1·m−2). 108 CHAPTER 7. DAY 7

Luminance (Y or Lᵥ,Ω) The radiance weighted by the eﬀect of each wavelength on a typical human observer, measured in SI units in candela per square meter (cd/m2). Often the term luminance is used for the relative luminance, Y/Yn, where Yn is the luminance of the reference white point.

Luma (Y′) The weighted sum of gamma-corrected R′, G′, and B′ values, and used in Y′CbCr, for JPEG compression and video transmission.

Brightness The “attribute of a visual sensation according to which an area appears to emit more or less light”.

Lightness, value The “brightness relative to the brightness of a similarly illuminated white”.

Colorfulness The “attribute of a visual sensation according to which the perceived color of an area appears to be more or less chromatic”.

Chroma The “colorfulness relative to the brightness of a similarly illuminated white”.

Saturation The “colorfulness of a stimulus relative to its own brightness”.

Brightness and colorfulness are absolute measures, which usually describe the spectral distribution of light entering the eye, while lightness and chroma are measured relative to some white point, and are thus often used for descriptions of surface colors, remaining roughly constant even as brightness and colorfulness change with diﬀerent illumination. Saturation can be deﬁned as either the ratio of colorfulness to brightness or of chroma to lightness.

General approach

HSL, HSV, and related models can be derived via geometric strategies, or can be thought of as speciﬁc instances of a “generalized LHS model”. The HSV and HSL model-builders took an RGB cube—with constituent amounts of red, green, and blue light in a color denoted R, G, B ∈ [0, 1][16]—and tilted it on its corner, so that black rested at the origin with white directly above it along the vertical axis, then measured the hue of the colors in the cube by their angle around that axis, starting with red at 0°. Then they came up with a characterization of brightness/value/lightness, and deﬁned saturation to range from 0 along the axis to 1 at the most colorful point for each pair of other parameters.[3][8][9]

Hue and chroma

In each of our models, we calculate both hue and what this article will call chroma, after Joblove and Greenberg, in the same way—that is, the hue of a color has the same numerical values in all of these models, as does its chroma. If we take our tilted RGB cube, and project it onto the “chromaticity plane" perpendicular to the neutral axis, our projection takes the shape of a hexagon, with red, yellow, green, cyan, blue, and magenta at its corners (fig. 9). Hue is roughly the angle of the vector to a point in the projection, with red at 0°, while chroma is roughly the distance of the point from the origin.[17][18] More precisely, both hue and chroma in this model are defined with respect to the hexagonal shape of the projection. The chroma is the proportion of the distance from the origin to the edge of the hexagon. In the lower part of the adjacent diagram, this is the ratio of lengths OP/OP′, or alternately the ratio of the radii of the two hexagons. This ratio is the difference between the largest and smallest values among R, G, or B in a color. To make our definitions easier to write, we’ll define these maximum, minimum, and chroma component values as M, m, and C, respectively.[19]

M = max(R, G, B) m = min(R, G, B) C = M − m

To understand why chroma can be written as M − m, notice that any neutral color, with R = G = B, projects onto the origin and so has 0 chroma. Thus if we add or subtract the same amount from all three of R, G, and B, we move vertically within our tilted cube, and do not change the projection. Therefore, any two colors (R, G, B) and (R − m, G − m, B − m) project on the same point, and have the same chroma. The chroma of a color with one of its components equal to zero (m = 0) is simply the maximum of the other two components. This chroma is M in the particular case of a color with a zero component, and M − m in general. 7.3. HSL AND HSV 109

The hue is the proportion of the distance around the edge of the hexagon which passes through the projected point, originally measured on the range [0, 1) but now typically measured in degrees [0°, 360°). For points which project onto the origin in the chromaticity plane (i.e., grays), hue is undeﬁned. Mathematically, this deﬁnition of hue is written piecewise:[20]

 undefined, if C = 0  G−B mod6, if M = R H′ = C  B−R + 2, if M = G  C R−G C + 4, if M = B H = 60◦ × H′ Sometimes, neutral colors (i.e. with C = 0) are assigned a hue of 0° for convenience of representation. These definitions amount to a geometric warping of hexagons into circles: each side of the hexagon is mapped linearly onto a 60° arc of the circle (fig. 10). After such a transformation, hue is precisely the angle around the origin and chroma the distance from the origin: the angle and magnitude of the vector pointing to a color. Sometimes for image analysis applications, this hexagon-to-circle transformation is skipped, and hue and chroma (we’ll denote these H2 and C2) are defined by the usual cartesian-to-polar coordinate transformations (fig. 11). The easiest way to derive those is via a pair of cartesian chromaticity coordinates which we’ll call α and β:[21][22][23]

α = 1 (2R − G − B) 2√ 3 − β = 2 (G B) H = atan2(β, α) 2 √ 2 2 C2 = α + β (The atan2 function, a “two-argument arctangent”, computes the angle from a cartesian coordinate pair.)

Notice that these two definitions of hue (H and H2) nearly coincide, with a maximum difference between them for any color of about 1.12°—which occurs at twelve particular hues, for instance H = 13.38°, H2 = 12.26°—and with H = H2 for every multiple of 30°. The two definitions of chroma (C and C2) differ more substantially: they are equal at the corners of our hexagon, but at points halfway between two corners, such as H = H2 = 30°, we have C = 1, but C2 = √¾ ≈ 0.866, a difference of about 13.4%.

Lightness

While the definition of hue is relatively uncontroversial—it roughly satisfies the criterion that colors of the same perceived hue should have the same numerical hue—the definition of a lightness or value dimension is less obvious: there are several possibilities depending on the purpose and goals of the representation. Here are four of the most common (fig. 12; three of these are also shown in fig. 8):

• The simplest definition is just the average of the three components, in the HSI model called intensity (fig. 12a). This is simply the projection of a point onto the neutral axis—the vertical height of a point in our tilted cube. The advantage is that, together with Euclidean-distance calculations of hue and chroma, this representation preserves distances and angles from the geometry of the RGB cube.[22][24] 1 I = 3 (R + G + B) • In the HSV “hexcone” model, value is defined as the largest component of a color, our M above (fig. 12b). This places all three primaries, and also all of the “secondary colors”—cyan, yellow, and magenta—into a plane with white, forming a hexagonal pyramid out of the RGB cube.[8] V = M

• In the HSL “bi-hexcone” model, lightness is defined as the average of the largest and smallest color components (fig. 12c). This definition also puts the primary and secondary colors into a plane, but a plane passing halfway between white and black. The resulting color solid is a double-cone similar to Ostwald’s, shown above.[9] 1 L = 2 (M + m) 110 CHAPTER 7. DAY 7

• A more perceptually relevant alternative is to use luma, Y′, as a lightness dimension (fig. 12d). Luma is the weighted average of gamma-corrected R, G, and B, based on their contribution to perceived luminance, long used as the monochromatic dimension in color television broadcast. For the Rec. 709 primaries used in sRGB, Y′709 = 0.21R + 0.72G + 0.07B; for the Rec. 601 NTSC primaries, Y′601 ≈ 0.30R + 0.59G + 0.11B; for other primaries different coefficients should be used.[14][25][26]

′ Y601 = 0.299R + 0.587G + 0.114B

All four of these leave the neutral axis alone. That is, for colors with R = G = B, any of the four formulations yields a lightness equal to the value of R, G, or B. For a graphical comparison, see ﬁg. 13 below.

Saturation

If we encode colors in a hue/lightness/chroma or hue/value/chroma model (using the definitions from the previous two sections), not all combinations of lightness (or value) and chroma are meaningful: that is, half of the colors we can describe using H ∈ [0°, 360°), C ∈ [0, 1], and V ∈ [0, 1] fall outside the RGB gamut (the gray parts of the slices in figure 14). The creators of these models considered this a problem for some uses. For example, in a color selection interface with two of the dimensions in a rectangle and the third on a slider, half of that rectangle is made of unused space. Now imagine we have a slider for lightness: the user’s intent when adjusting this slider is potentially ambiguous: how should the software deal with out-of-gamut colors? Or conversely, If the user has selected as colorful as possible a dark purple , and then shifts the lightness slider upward, what should be done: would the user prefer to see a lighter purple still as colorful as possible for the given hue and lightness , or a lighter purple of exactly the same chroma as the original color ?[9] To solve problems such as these, the HSL and HSV models scale the chroma so that it always fits into the range [0, 1] for every combination of hue and lightness or value, calling the new attribute saturation in both cases (fig. 14). To calculate either, simply divide the chroma by the maximum chroma for that value or lightness.

{ 0, if V = 0 SHSV = C , otherwise { V 0, if L = 1 SHSL = C 1−|2L−1| , otherwise

The HSI model commonly used for computer vision, which takes H2 as a hue dimension and the component average I (“intensity”) as a lightness dimension, does not attempt to “fill” a cylinder by its definition of saturation. Instead of presenting color choice or modification interfaces to end users, the goal of HSI is to facilitate separation of shapes in an image. Saturation is therefore defined in line with the psychometric definition: chroma relative to lightness (fig. 15). See the Use in image analysis section of this article.[27]

{ 0, if I = 0 S = HSI − m 1 I , otherwise

Using the same name for these three different definitions of saturation leads to some confusion, as the three attributes describe substantially different color relationships; in HSV and HSI, the term roughly matches the psychometric definition, of a chroma of a color relative to its own lightness, but in HSL it does not come close. Even worse, the word saturation is also often used for one of the measurements we call chroma above (C or C2).

Examples

All parameter values shown below are in the interval [0, 1], except those for H and H2 which are in the interval [0°, 360°).[28] 7.3. HSL AND HSV 111

7.3.4 Use in end-user software

See also: Color tool and Image editing The original purpose of HSL and HSV and similar models, and their most common current application, is in color selection tools. At their simplest, some such color pickers provide three sliders, one for each attribute. Most, however, show a two-dimensional slice through the model, along with a slider controlling which particular slice is shown. The latter type of GUI exhibits great variety, because of the choice of cylinders, hexagonal prisms, or cones/bicones that the models suggest (see the diagram near the top of the page). Several color choosers from the 1990s are shown to the right, most of which have remained nearly unchanged in the intervening time: today, nearly every computer color chooser uses HSL or HSV, at least as an option. Some more sophisticated variants are designed for choosing whole sets of colors, basing their suggestions of compatible colors on the HSL or HSV relationships between them.[30] Most web applications needing color selection also base their tools on HSL or HSV, and pre-packaged open source color choosers exist for most major web front-end frameworks. The CSS 3 specification allows web authors to specify colors for their pages directly with HSL coordinates.[31] HSL and HSV are sometimes used to define gradients for data visualization, as in maps or medical images. For example, the popular GIS program ArcGIS historically applied customizable HSV-based gradients to numerical geographical data.[32] Image editing software also commonly includes tools for adjusting colors with reference to HSL or HSV coordinates, or to coordinates in a model based on the “intensity” or luma defined above. In particular, tools with a pair of “hue” and “saturation” sliders are commonplace, dating to at least the late-1980s, but various more complicated color tools have also been implemented. For instance, the Unix image viewer and color editor xv allowed six user-definable hue (H) ranges to be rotated and resized, included a dial-like control for saturation (SHSV), and a curves-like interface for controlling value (V)—see fig. 17. The image editor Picture Window Pro includes a “color correction” tool which affords complex remapping of points in a hue/saturation plane relative to either HSL or HSV space.[33] Video editors also use these models. For example, both Avid and Final Cut Pro include color tools based on HSL or a similar geometry for use adjusting the color in video. With the Avid tool, users pick a vector by clicking a point within the hue/saturation circle to shift all the colors at some lightness level (shadows, mid-tones, highlights) by that vector. Since version 4.0, Adobe Photoshop’s “Luminosity”, “Hue”, “Saturation”, and “Color” blend modes composite layers using a luma/chroma/hue color geometry. These have been copied widely, but several imitators use the HSL (e.g. PhotoImpact, Paint Shop Pro) or HSV (e.g. GIMP) geometries instead.[34]

7.3.5 Use in image analysis

See also: Computer vision and Image analysis

HSL, HSV, HSI, or related models are often used in computer vision and image analysis for feature detection or image segmentation. The applications of such tools include object detection, for instance in robot vision; object recognition, for instance of faces, text, or license plates; content-based image retrieval; and analysis of medical images.[27] For the most part, computer vision algorithms used on color images are straightforward extensions to algorithms designed for grayscale images, for instance k-means or fuzzy clustering of pixel colors, or canny edge detection. At the simplest, each color component is separately passed through the same algorithm. It is important, therefore, that the features of interest can be distinguished in the color dimensions used. Because the R, G, and B components of an object’s color in a digital image are all correlated with the amount of light hitting the object, and therefore with each other, image descriptions in terms of those components make object discrimination difficult. Descriptions in terms of hue/lightness/chroma or hue/lightness/saturation are often more relevant.[27] Starting in the late 1970s, transformations like HSV or HSI were used as a compromise between effectiveness for segmentation and computational complexity. They can be thought of as similar in approach and intent to the neural processing used by human color vision, without agreeing in particulars: if the goal is object detection, roughly separating hue, lightness, and chroma or saturation is effective, but there is no particular reason to strictly mimic human color response. John Kender’s 1976 master’s thesis proposed the HSI model. Ohta et al. (1980) instead used a model made up of dimensions similar to those we have called I, α, and β. In recent years, such models have continued to see wide use, as their performance compares favorably with more complex models, and their computational simplicity remains compelling.[35][27][36][37][38] 112 CHAPTER 7. DAY 7

7.3.6 Disadvantages

While HSL, HSV, and related spaces serve well enough to, for instance, choose a single color, they ignore much of the complexity of color appearance. Essentially, they trade off perceptual relevance for computation speed, from a time in computing history (high-end 1970s graphics workstations, or mid-1990s consumer desktops) when more sophisticated models would have been too computationally expensive.[39] HSL and HSV are simple transformations of RGB which preserve symmetries in the RGB cube unrelated to human perception, such that its R, G, and B corners are equidistant from the neutral axis, and equally spaced around it. If we plot the RGB gamut in a more perceptually-uniform space, such as CIELAB (see below), it becomes immediately clear that the red, green, and blue primaries do not have the same lightness or chroma, or evenly spaced hues. Furthermore, different RGB displays use different primaries, and so have different gamuts. Because HSL and HSV are defined purely with reference to some RGB space, they are not absolute color spaces: to specify a color precisely requires reporting not only HSL or HSV values, but also the characteristics of the RGB space they are based on, including the gamma correction in use. If we take an image and extract the hue, saturation, and lightness or value components, and then compare these to the components of the same name as defined by color scientists, we can quickly see the difference, perceptually. For example, examine the following images of a fire breather (fig. 13). CIELAB L* is a CIE-defined quantity intended to match perceptual lightness response, and it is plain that L* appears similar in lightness to the original color image. Luma is roughly similar, but differs somewhat at high chroma. HSL L and HSV V, by contrast, diverge substantially from perceptual lightness. Though none of the dimensions in these spaces match their perceptual analogs, the value of HSV and the saturation of HSL are particular offenders. In HSV, the blue primary and white are held to have the same value, even though perceptually the blue primary has somewhere around 10% of the luminance of white (the exact fraction depends on the particular RGB primaries in use). In HSL, a mix of 100% red, 100% green, 90% blue—that is, a very light yellow —is held to have the same saturation as the green primary , even though the former color has almost no chroma or saturation by the conventional psychometric definitions. Such perversities led Cynthia Brewer, expert in color scheme choices for maps and information displays, to tell the American Statistical Association:

Computer science offers a few poorer cousins to these perceptual spaces that may also turn up in your software interface, such as HSV and HLS. They are easy mathematical transformations of RGB, and they seem to be perceptual systems because they make use of the hue–lightness/value–saturation terminology. But take a close look; don’t be fooled. Perceptual color dimensions are poorly scaled by the color specifications that are provided in these and some other systems. For example, saturation and lightness are confounded, so a saturation scale may also contain a wide range of lightnesses (for example, it may progress from white to green which is a combination of both lightness and saturation). Likewise, hue and lightness are confounded so, for example, a saturated yellow and saturated blue may be designated as the same ‘lightness’ but have wide differences in perceived lightness. These flaws make the systems difficult to use to control the look of a color scheme in a systematic manner. If much tweaking is required to achieve the desired effect, the system offers little benefit over grappling with raw specifications in RGB or CMY.[40]

If these problems make HSL and HSV problematic for choosing colors or color schemes, they make them much worse for image adjustment. HSL and HSV, as Brewer mentioned, confound perceptual color-making attributes, so that changing any dimension results in non-uniform changes to all three perceptual dimensions, and distorts all of the color relationships in the image. For instance, rotating the hue of a pure dark blue toward green will also reduce its perceived chroma, and increase its perceived lightness (the latter is grayer and lighter), but the same hue rotation will have the opposite impact on lightness and chroma of a lighter bluish-green— to (the latter is more colorful and slightly darker). In the example below (fig. 21), the image on the left (a) is the original photograph of a green turtle. In the middle image (b), we have rotated the hue (H) of each color by −30°, while keeping HSV value and saturation or HSL lightness and saturation constant. In the image on the right (c), we make the same rotation to the HSL/HSV hue of each color, but then we force the CIELAB lightness (L*, a decent approximation of perceived lightness) to remain constant. Notice how the hue-shifted middle version without such a correction dramatically changes the perceived lightness relationships between colors in the image. In particular, the turtle’s shell is much darker and has less contrast, and the background water is much lighter. Because hue is a circular quantity, represented numerically with a discontinuity at 360°, it is difficult to use in statistical computations or quantitative comparisons: analysis requires the use of circular statistics. Furthermore, hue is defined 7.3. HSL AND HSV 113 piecewise, in 60° chunks, where the relationship of lightness, value, and chroma to R, G, and B depends on the hue chunk in question. This definition introduces discontinuities, corners which can plainly be seen in horizontal slices of HSL or HSV.[41][42] Charles Poynton, digital video expert, lists the above problems with HSL and HSV in his Color FAQ, and concludes that:

HSB and HLS were developed to specify numerical Hue, Saturation and Brightness (or Hue, Light- ness and Saturation) in an age when users had to specify colors numerically. The usual formulations of HSB and HLS are ﬂawed with respect to the properties of color vision. Now that users can choose colors visually, or choose colors related to other media (such as PANTONE), or use perceptually-based systems like L*u*v* and L*a*b*, HSB and HLS should be abandoned.[43]

7.3.7 Other cylindrical-coordinate color models

Fig. 22. Runge’s Farbenkugel, 1810.

Fig. 23. Munsell’s balanced color sphere, 1900, from A Color Notation, 1905. See also: Color solid

The creators of HSL and HSV were far from the first to imagine colors fitting into conic or spherical shapes, with neutrals running from black to white in a central axis, and hues corresponding to angles around that axis. Similar arrangements date back to the 18th century, and continue to be developed in the most modern and scientific models. A pair of the most influential older models are Philipp Otto Runge’s 1810 Farbenkugel (color sphere), and the early- 20th-century Munsell color system. Albert Munsell began with a spherical arrangement in his 1905 book A Color Notation, but he wished to properly separate color-making attributes into separate dimensions, which he called hue, value, and chroma, and after taking careful measurements of perceptual responses, he realized that no symmetrical shape would do, so he reorganized his system into a lumpy blob.[44] Munsell’s system became extremely popular, the de facto reference for American color standards—used not only for specifying the color of paints and crayons, but also, e.g., electrical wire, beer, and soil color—because it was organized based on perceptual measurements, specified colors via an easily learned and systematic triple of numbers, because the 114 CHAPTER 7. DAY 7

color chips sold in the Munsell Book of Color covered a wide gamut and remained stable over time (rather than fading), and because it was effectively marketed by Munsell’s Company. In the 1940s, the Optical Society of America made extensive measurements, and adjusted the arrangement of Munsell colors, issuing a set of “renotations”. The trouble with the Munsell system for computer graphics applications is that its colors are not specified via any set of simple equations, but only via its foundational measurements: effectively a lookup table. Converting from RGB ↔ Munsell requires interpolating between that table’s entries, and is extremely computationally expensive in comparison with converting from RGB ↔ HSL or RGB ↔ HSV which only requires a few simple arithmetic operations.[45][46][47][48] In densitometry, a model quite similar to the hue defined above is used for describing colors of CMYK process inks. In 1953, Frank Preucil developed two geometric arrangements of hue, the “Preucil hue circle” and the “Preucil hue hexagon”, analogous to our H and H2, respectively, but defined relative to idealized cyan, yellow, and magenta ink colors. The Preucil hue error of an ink indicates the difference in the “hue circle” between its color and the hue of the corresponding idealized ink color. The grayness of an ink is m/M, where m and M are the minimum and maximum among the amounts of idealized cyan, magenta, and yellow in a density measurement.[49] The Swedish Natural Color System (NCS), widely used in Europe, takes a similar approach to the Ostwald bicone shown earlier. Because it attempts to fit color into a familiarly shaped solid based on "phenomenological" instead of photometric or psychological characteristics, it suffers from some of the same disadvantages as HSL and HSV: in particular, its lightness dimension differs from perceived lightness, because it forces colorful yellow, red, green, and blue into a plane.[50] The International Commission on Illumination (CIE) developed the XYZ model for describing the colors of light spectra in 1931, but its goal was to match human visual metamerism, rather than to be perceptually uniform, geomet- rically. In the 1960s and 70s, attempts were made to transform XYZ colors into a more relevant geometry, influenced by the Munsell system. These efforts culminated in the 1976 CIELUV and CIELAB models. The dimensions of these models—(L*, u*, v*) and (L*, a*, b*), respectively—are cartesian, based on the opponent process theory of color, but both are also often described using polar coordinates—(L*, C*uv, h*uv) or (L*, C*ab, h*ab) and also HCL, where L* is lightness, C* is chroma, and h* is hue angle. Officially, both CIELAB and CIELUV were created for their color difference metrics ∆E*ab and ∆E*uv, particularly for use defining color tolerances, but both have become widely used as color order systems and color appearance models, including in computer graphics and computer vision. For example, gamut mapping in ICC color management is usually performed in CIELAB space, and Adobe Photoshop includes a CIELAB mode for editing images. CIELAB and CIELUV geometries are much more perceptually relevant than many others such as RGB, HSL, HSV, YUV/YIQ/YCbCr or XYZ, but are not perceptually perfect, and in particular have trouble adapting to unusual lighting conditions.[45][51][52][53] The CIE’s most recent model, CIECAM02 (CAM stands for “color appearance model”), is more theoretically sophisticated and computationally complex than earlier models. Its aims are to fix several of the problems with models such as CIELAB and CIELUV, and to explain not only responses in carefully controlled experimental environments, but also to model the color appearance of real-world scenes. Its dimensions J (lightness), C (chroma), and h (hue) define a polar-coordinate geometry.[45][50]

7.3.8 Converting to RGB

To convert from HSL or HSV to RGB, we essentially invert the steps listed above (as before, R, G, B ∈ [0, 1]). First, we compute chroma, by multiplying saturation by the maximum chroma for a given lightness or value. Next, we ﬁnd the point on one of the bottom three faces of the RGB cube which has the same hue and chroma as our color (and therefore projects onto the same point in the chromaticity plane). Finally, we add equal amounts of R, G, and B to reach the proper lightness or value.[18]

From HSV

Given a color with hue H ∈ [0°, 360°), saturation SHSV ∈ [0, 1], and value V ∈ [0, 1], we ﬁrst ﬁnd chroma:

C = V × SHSV

Then we can ﬁnd a point (R1, G1, B1) along the bottom three faces of the RGB cube, with the same hue and chroma as our color (using the intermediate value X for the second largest component of this color): 7.3. HSL AND HSV 115

H H′ = 60◦ X = C × (1 − |H′ mod2 − 1|)  (0, 0, 0) if H is undeﬁned   ′ (C,X, 0) if 0 ≤ H ≤ 1  ′ (X,C, 0) if 1 ≤ H ≤ 2 ≤ ′ ≤ (R1,G1,B1) = (0,C,X) if 2 H 3  ′ (0,X,C) if 3 ≤ H ≤ 4  (X, 0,C) if 4 ≤ H′ ≤ 5  (C, 0,X) if 5 ≤ H′ < 6

Overlap (when H′ is an integer) occurs because two ways to calculate the value are equivalent: X = 0 or X = C , as appropriate. Finally, we can ﬁnd R, G, and B by adding the same amount to each component, to match value:

m = V − C

(R, G, B) = (R1 + m, G1 + m, B1 + m)

From HSL

Given an HSL color with hue H ∈ [0°, 360°), saturation SHSL ∈ [0, 1], and lightness L ∈ [0, 1], we can use the same strategy. First, we ﬁnd chroma:

C = (1 − |2L − 1|) × SHSL

Then we can, again, ﬁnd a point (R1, G1, B1) along the bottom three faces of the RGB cube, with the same hue and chroma as our color (using the intermediate value X for the second largest component of this color):

H H′ = 60◦ X = C × (1 − |H′ mod2 − 1|)  (0, 0, 0) if H is undeﬁned   ′ (C,X, 0) if 0 ≤ H ≤ 1  ′ (X,C, 0) if 1 ≤ H ≤ 2 ≤ ′ ≤ (R1,G1,B1) = (0,C,X) if 2 H 3  ′ (0,X,C) if 3 ≤ H ≤ 4  (X, 0,C) if 4 ≤ H′ ≤ 5  (C, 0,X) if 5 ≤ H′ < 6

Overlap (when H′ is an integer) occurs because two ways to calculate the value are equivalent: X = 0 or X = C , as appropriate. Finally, we can ﬁnd R, G, and B by adding the same amount to each component, to match lightness:

− 1 m = L 2 C (R, G, B) = (R1 + m, G1 + m, B1 + m) 116 CHAPTER 7. DAY 7

From HSI

Given an HSI color with hue H ∈ [0°, 360°), saturation SHSI ∈ [0, 1], and intensity I ∈ [0, 1], we can use the same strategy, in a slightly diﬀerent order:

H H′ = 60◦ Z = 1 − |H′ mod2 − 1| 3 × I × S C = HSI 1 + Z X = C × Z

Where C is the chroma.

Then we can, again, ﬁnd a point (R1, G1, B1) along the bottom three faces of the RGB cube, with the same hue and chroma as our color (using the intermediate value X for the second largest component of this color):

 (0, 0, 0) if H is undeﬁned   ′ (C,X, 0) if 0 ≤ H ≤ 1  ′ (X,C, 0) if 1 ≤ H ≤ 2 ≤ ′ ≤ (R1,G1,B1) = (0,C,X) if 2 H 3  ′ (0,X,C) if 3 ≤ H ≤ 4  (X, 0,C) if 4 ≤ H′ ≤ 5  (C, 0,X) if 5 ≤ H′ < 6

Overlap (when H′ is an integer) occurs because two ways to calculate the value are equivalent: X = 0 or X = C , as appropriate. Finally, we can ﬁnd R, G, and B by adding the same amount to each component, to match lightness:

m = I × (1 − SHSI )

(R, G, B) = (R1 + m, G1 + m, B1 + m)

From luma/chroma/hue

[54] Given a color with hue H ∈ [0°, 360°), chroma C ∈ [0, 1], and luma Y′601 ∈ [0, 1], we can again use the same strategy. Since we already have H and C, we can straightaway ﬁnd our point (R1, G1, B1) along the bottom three faces of the RGB cube:

H H′ = 60◦ X = C × (1 − |H′ mod2 − 1|)  (0, 0, 0) if H is undeﬁned   ′ (C,X, 0) if 0 ≤ H ≤ 1  ′ (X,C, 0) if 1 ≤ H ≤ 2 ≤ ′ ≤ (R1,G1,B1) = (0,C,X) if 2 H 3  ′ (0,X,C) if 3 ≤ H ≤ 4  (X, 0,C) if 4 ≤ H′ ≤ 5  (C, 0,X) if 5 ≤ H′ < 6 Overlap (when H′ is an integer) occurs because two ways to calculate the value are equivalent: X = 0 or X = C , as appropriate. 7.3. HSL AND HSV 117

Then we can ﬁnd R, G, and B by adding the same amount to each component, to match luma:

′ − m = Y601 (.30R1 + .59G1 + .11B1)

(R, G, B) = (R1 + m, G1 + m, B1 + m)

7.3.9 Swatches

Mouse over the swatches below to see the R, G, and B values for each swatch in a tooltip.

HSV

HSL

7.3.10 Notes and references

[1] In Joblove and Greenberg’s (1978) paper ﬁrst introducing HSL, they called HSL lightness “intensity”, called HSL saturation “relative chroma”, called HSV saturation “saturation” and called HSV value “value”. They carefully and unambiguously described and compared three models: hue/chroma/intensity, hue/relative chroma/intensity, and hue/value/saturation. Un- fortunately, later authors were less fastidious, and current usage of these terms is inconsistent and often misleading.

[2] The name hexcone for hexagonal pyramid was coined in Smith, and stuck.

[3] Levkowitz and Herman

[4] Wilhelm Ostwald (1916). Die Farbenﬁbel. Leipzig. Wilhelm Ostwald (1918). Die Harmonie der Farben. Leipzig.

[5] Gar A. Bergstedt (April 1983). US patent 4694286, “Apparatus and method for modifying displayed color images”. Filed 1983-04-08. Issued 1987-09-15. Assigned to Tektronix, Inc.

[6] For instance, a 1982 study by Berk, et al., found that users were better at describing colors in terms of HSL than RGB coordinates, after being taught both systems, but were much better still at describing them in terms of the natural-language CNS model (which uses names such as “very dark grayish yellow-green” or “medium strong bluish purple”). This shouldn’t be taken as gospel however: a 1987 study by Schwarz, et al., found that users could match colors using RGB controls faster than with HSL controls; a 1999 study by Douglas and Kirkpatrick found that the visual feedback in the user interface mattered more than the particular color model in use, for user matching speed. Toby Berk; Arie Kaufman; Lee Brownston (August 1982). “A human factors study of color notation systems for computer graphics”. Communications of the ACM. 25 (8): 547–550. doi:10.1145/358589.358606. Michael W. Schwarz; William B. Cowan; John C. Beatty (April 1987). “An experimental comparison of RGB, YIQ, LAB, HSV, and opponent color models”. ACM Transactions on Graphics. 6 (2): 123–158. doi:10.1145/31336.31338. Sarah A. Douglas; Arthur E. Kirkpatrick (April 1999). “Model and representation: the eﬀect of visual feedback on human performance in a color picker interface”. ACM Transactions on Graphics. 18 (2): 96–127. doi:10.1145/318009.318011.

[7] Maureen C. Stone (August 2001). “A Survey of Color for Computer Graphics”. Course at SIGGRAPH 2001.

[8] Smith

[9] Joblove and Greenberg

[10] Ware Myers (July 1979). “Interactive Computer Graphics: Flying High-Part I”. Computer. 12 (7): 8–17. doi:10.1109/MC.1979.1658808.

[11] N. Magnetat-Thalmann; N. Chourot; D. Thalmann (March 1984). “Colour Gradation, Shading and Texture Using a Lim- ited Terminal”. Computer Graphics Forum. 3: 83. doi:10.1111/j.1467-8659.1984.tb00092.x.

[12] Computer Graphics Staﬀ (August 1979). “Status Report of the Graphics Standards Planning Committee”. ACM SIG- GRAPH Computer Graphics. 13 (3): 1. doi:10.1145/988497.988498.

[13] Mark Fairchild: “Clearly, if color appearance is to be described in a systematic, mathematical way, deﬁnitions of the phenomena being described need to be precise and universally agreed upon.” For the deﬁnitions of color-making attributes which follow, see: Fairchild 2005, pp. 83–93 (this is the source of the direct quotations). Kuehni ASTM (2009). Standard Terminology of Appearance. E284-09a. CIE (1987). International Lighting Vocabulary. Number 17.4. CIE, 4th edition. ISBN 978-3-900734-07-7. 118 CHAPTER 7. DAY 7

[14] Poynton

[15] Sharma, G. (2003). Digital Color Imaging Handbook. Boca Raton, FL: CRC Press. ISBN 0-8493-0900-X.

[16] In Levkowitz and Herman’s formulation, R, G, and B stand for the voltages on the guns of a CRT display, which might have different maxima, and so their cartesian gamut could be a box of any unequal dimensions. Other definitions commonly use integer values in the range [0, 255], storing the value for each component in one byte. We define the RGB gamut to be a unit cube for convenience, because it simplifies and clarifies the math. Also, in general, HSL and HSV are today computed directly from gamma-corrected R′, G′, and B′—for instance in sRGB space—but, when the models were developed, might have been transformations of a linear RGB space. Early authors don’t address gamma correction at all. We will drop the primes, and the labels R, G, and B should be taken to stand for the three attributes of the origin RGB space, whether or not it is gamma corrected.

[17] Using the chroma here not only agrees with the original Joblove and Greenberg paper, but is also in the proper spirit of the psychometric definition of the term. Some models call this attribute saturation—for instance Adobe Photoshop’s “Saturation” blend mode—but such use is even more confusing than the use of the term in HSL or HSV, especially when two substantially different definitions are used side by side.

[18] Most of the computer graphics papers and books discussing HSL or HSV have a formula or algorithm describing them formally. Our formulas which follow are some mix of those. See, for instance, Agoston or Foley

[19] Hanbury and Serra put a great deal of eﬀort into explaining why what we call chroma here can be written as max(R, G, B) − min(R, G, B), and showing that this value is a seminorm. They reserve the name chroma for the Euclidean norm in the chromaticity plane (our C2), and call this hexagonal distance saturation instead, as part of their IHLS model

[20] In the following, the multiplication of hue by 60°—that is, 360°/6—can be seen as the hexagonal-geometry analogue of the conversion from radians to degrees, a multiplication by 360°/2π: the circumference of a unit circle is 2π; the circumference of a unit hexagon is 6.

[21] Hanbury and Serra (2002)

[22] Allan Hanbury (2008). “Constructing cylindrical coordinate colour spaces” (PDF). Pattern Recognition Letters. 29 (4): 494. doi:10.1016/j.patrec.2007.11.002.

[23] Patrick Lambert; Thierry Carron (1999). “Symbolic fusion of luminance-hue-chroma features for region segmentation”. Pattern Recognition. 32 (11): 1857. doi:10.1016/S0031-3203(99)00010-2.

[24] Rafael C. Gonzalez and Richard Eugene Woods (2008). Digital Image Processing, 3rd ed. Upper Saddle River, NJ: Prentice Hall. ISBN 0-13-168728-X. pp. 407–413.

[25] For a more speciﬁc discussion of the term luma, see Charles Poynton (1999). "YUV and luminance considered harmful: A plea for precise terminology in video”. www.poynton.com. Accessed January 2010.

[26] See also RGB color space#Speciﬁcations. Photoshop exclusively uses the NTSC coeﬃcients for its “Luminosity” blend mode regardless of the RGB color space involved. See: Bruce Lindbloom (2001-09-25). “Re: Luminosity channel...”. colorsync-users mailing list.

[27] Heng-Da Cheng; Xihua Jiang; Angela Sun; Jingli Wang (2001). “Color image segmentation: Advances and prospects”. Pattern Recognition. 34 (12): 2259. doi:10.1016/S0031-3203(00)00149-7. This computer vision literature review brieﬂy summarizes research in color image segmentation, including that using HSV and HSI representations.

[28] The ﬁrst nine colors in this table were chosen by hand, and the last ten colors were chosen at random.

[29] See Smith. Many of these screenshots were taken from the GUIdebook, and the rest were gathered from image search results.

[30] For instance, a tool in Illustrator CS4, and Adobe’s related web tool, Kuler, both allow users to deﬁne color schemes based on HSV relationships, but with a hue circle modiﬁed to better match the RYB model used traditionally by painters. The web tools ColorJack, Color Wizard, and ColorBlender all pick color schemes with reference to HSL or HSV.

[31] Try a web search for "«framework name» color picker” for examples for a given framework, or "JavaScript color picker” for general results. Tantek Çelik, Chris Lilley, and L. David Baron (July 2008). “CSS3 Color Module”. W3C Working Draft 21 July 2008.

[32] ArcGIS calls its map-symbol gradients “color ramps”. Current versions of ArcGIS can use CIELAB instead for deﬁning them. ESRI (January 2008). “Working with color ramps”. ArcGIS 9.2 Help. Accessed February 2010. 7.3. HSL AND HSV 119

[33] For instance, the ﬁrst version of Photoshop had an HSL-based tool; see “Photoshop hue/saturation” in the GUIdebook for screenshots. John Bradley (1994). XV 3.10a Manual. “The HSV Modiﬁcation Tools” Kiril Sinkel (January 2010). User Guide for Picture Window and Picture Window Pro. Digital Light & Color.

[34] Photoshop’s documentation explains that, e.g., “Luminosity: Creates a result color with the hue and saturation of the base color and the luminance of the blend color.” “List of Blending Modes”. Adobe Help Resource Center.

[35] The Ohta et al. model has parameters I1 = (R + G + B)/3, I2 = (R − B)/2, I3 = (2G − R − B)/4. I1 is the same as our I, and I2 and I3 are similar to our β and α, respectively, except that (a) where α points in the direction of R in the “chromaticity plane”, I3 points in the direction of G, and (b) the parameters have a diﬀerent linear scaling which avoids the √3 of our β.

[36] John Kender (1976). “Saturation, hue and normalized color”. Carnegie Mellon University, Computer Science Dept. Pitts- burgh, PA.

[37] Yu-Ichi Ohta; Takeo Kanade; Toshiyuki Sakai (1980). “Color information for region segmentation”. Computer Graphics and Image Processing. 13 (3): 222. doi:10.1016/0146-664X(80)90047-7.

[38] Ffrank Perez; Christof Koch (1994). “Toward color image segmentation in analog VLSI: Algorithm and hardware”. In- ternational Journal of Computer Vision. 12: 17. doi:10.1007/BF01420983.

[39] Most of the disadvantages below are listed in Poynton, though as mere statements, without examples.

[40] The text of Brewer’s presentation to the ASA is online, “Color Use Guidelines for Data Representation”. The published paper is Cynthia A. Brewer (1999). “Color Use Guidelines for Data Representation”, Proceedings of the Section on Statistical Graphics. Alexandria, VA: American Statistical Association. pp. 55–60.

[41] Hanbury, Allan (2003). Circular Statistics Applied to Colour Images. 8th Computer Vision Winter Workshop. CiteSeerX 10.1.1.4.1381 .

[42] Circular statistics are described in the textbook Fisher, Nicholas (1996). Statistical Analysis of Circular Data. Cambridge, England: Cambridge University Press.

[43] Charles Poynton (1997). “What are HSB and HLS?" poynton.com

[44] Philipp Otto Runge (1810). Die Farben-Kugel, oder Construction des Verhaeltnisses aller Farben zueinander. Hamburg, Germany: Perthes. Albert Henry Munsell (1905). A Color Notation. Boston, MA: Munsell Color Company. See also Fairchild, and Munsell Color System and its references.

[45] Fairchild

[46] Edward Landa and Mark Fairchild (September–October 2005). “Charting Color from the Eye of the Beholder”. American Scientist 93(5): 436

[47] Dorothy Nickerson (1976). “History of the Munsell Color System”. Color Research and Application. 1: 121–130.

[48] Sidney Newhall; Dorothy Nickerson; Deane Judd (1943). “Final Report of the OSA Subcommittee on the Spacing of the Munsell Colors”. Journal of the Optical Society of America. 33 (7): 385. doi:10.1364/JOSA.33.000385.

[49] Frank Preucil (1953). “Color Hue and Ink Transfer—Their Relation to Perfect Reproduction”. Proceedings of the 5th Annual Technical Meeting of TAGA. pp. 102–110. See also Hue.

[50] MacEvoy

[51] Kuehni

[52] Robert Hunt (2004). The Reproduction of Colour. 6th ed. MN: Voyageur Press. ISBN 0-86343-368-5.

[53] MacEvoy 2010. “Modern Color Models” Adobe (January 2007). “The Lab Color Mode in Photoshop”. Technical Note 310838. Steven K. Shevell (2003) The Science of Color. 2nd ed. Elsevier Science & Technology. ISBN 0-444-51251-9. pp. 202– 206 See also CIELAB, CIELUV, Color diﬀerence, Color management, and their references.

[54] Some points in this cylinder fall out of gamut. 120 CHAPTER 7. DAY 7

7.3.11 Bibliography

• Agoston, Max K. (2005). Computer Graphics and Geometric Modeling: Implementation and Algorithms. Lon- don: Springer. pp. 300–306. ISBN 1-85233-818-0. Agoston’s book contains a description of HSV and HSL, and algorithms in pseudocode for converting to each from RGB, and back again. • Fairchild, Mark D. (2005). Color Appearance Models (2nd ed.). Addison-Wesley. This book doesn’t discuss HSL or HSV speciﬁcally, but is one of the most readable and precise resources about current color science. • Foley, J. D.; et al. (1995). Computer Graphics: Principles and Practice (2nd ed.). Redwood City, CA: Addison- Wesley. ISBN 0-201-84840-6. The standard computer graphics textbook of the 1990s, this tome has a chapter full of algorithms for converting between color models, in C.

• Allan Hanbury; Jean Serra (December 2002). A 3D-polar Coordinate Colour Representation Suitable for Image Analysis. Pattern Recognition and Image Processing Group Technical Report 77. Vienna, Austria: Vienna University of Technology. • Joblove, George H.; Greenberg, Donald (August 1978). “Color spaces for computer graphics”. Computer Graphics. 12 (3): 20–25. doi:10.1145/965139.807362. Joblove and Greenberg’s paper was the ﬁrst describing the HSL model, which it compares to HSV. • Kuehni, Rolf G. (2003). Color Space and Its Divisions: Color Order from Antiquity to the present. New York: Wiley. ISBN 978-0-471-32670-0. This book only brieﬂy mentions HSL and HSV, but is a comprehensive description of color order systems through history.

• Levkowitz, Haim; Herman, Gabor T. (1993). “GLHS: A generalised lightness, hue and saturation color model”. CVGIP: Graphical Models and Image Processing. 55 (4): 271–285. doi:10.1006/cgip.1993.1019. This paper explains how both HSL and HSV, as well as other similar models, can be thought of as speciﬁc variants of a more general “GLHS” model. Levkowitz and Herman provide pseudocode for converting from RGB to GLHS and back. • MacEvoy, Bruce (January 2010). “Color Vision”. handprint.com.. Especially the sections about “Modern Color Models” and “Modern Color Theory”. MacEvoy’s extensive site about color science and paint mixing is one of the best resources on the web. On this page, he explains the color-making attributes, and the general goals and history of color order systems—including HSL and HSV—and their practical relevance to painters. • Poynton, Charles (1997). “Frequently Asked Questions About Color”. This self-published frequently asked questions page, by digital video expert Charles Poynton, explains, among other things, why in his opinion these models “are useless for the speciﬁcation of accurate color”, and should be abandoned in favor of more psychometrically relevant models. • Smith, Alvy Ray (August 1978). “Color gamut transform pairs”. Computer Graphics. 12 (3): 12–19. doi:10.1145/965139.807361. This is the original paper describing the “hexcone” model, HSV. Smith was a researcher at NYIT’s Computer Graphics Lab. He describes HSV’s use in an early digital painting program.

7.3.12 External links

• Demonstrative color conversion applet • HSV Colors by Hector Zenil, The Wolfram Demonstrations Project. 7.3. HSL AND HSV 121

Fig. 8. The geometric derivation of the cylindrical HSL and HSV representations of an RGB “colorcube”. 122 CHAPTER 7. DAY 7

Fig. 9. Both hue and chroma are deﬁned based on the projection of the RGB cube onto a hexagon in the “chromaticity plane”. Chroma is the relative size of the hexagon passing through a point, and hue is how far around that hexagon’s edge the point lies. 7.3. HSL AND HSV 123

Fig. 10. The deﬁnitions of hue and chroma in HSL and HSV have the eﬀect of warping hexagons into circles.

Fig. 11. Constructing rectangular chromaticity coordinates α and β, and then transforming those into hue H2 and chroma C2 yields slightly diﬀerent values than computing hexagonal hue H and chroma C: compare the numbers in this diagram to those earlier in this section. 124 CHAPTER 7. DAY 7

Fig. 12a–d. Four diﬀerent possible “lightness” dimensions, plotted against chroma, for a pair of complementary hues. Each plot is a vertical cross-section of its three-dimensional color solid. 7.3. HSL AND HSV 125

Fig. 14a–d. In both HSL and HSV, saturation is simply the chroma scaled to ﬁll the interval [0, 1] for every combination of hue and lightness or value. 126 CHAPTER 7. DAY 7

Fig. 15a–b. In HSI, saturation, shown in the slice on the right, is roughly the chroma relative to lightness. Also common is a model with dimensions I, H2, C2, shown in the slice on the left. Notice that the hue in these slices is the same as the hue above, but H diﬀers slightly from H2. 7.3. HSL AND HSV 127

Fig 16a–g. By the 1990s, HSL and HSV color selection tools were ubiquitous. The screenshots above are taken from: (a) SGI IRIX 5, c. 1995; (b) Adobe Photoshop, c. 1990; (c) IBM OS/2 Warp 3, c. 1994; (d) Apple Macintosh System 7, c. 1996; (e) Fractal Design Painter, c. 1993; (f) Microsoft Windows 3.1, c. 1992; (g) NeXTSTEP, c. 1995. These are undoubtedly based on earlier examples, stretching back to PARC and NYIT in the mid-1970s.[29] 128 CHAPTER 7. DAY 7

1

V

V (1 - S)

0 0° 60° 120° 180° 240° 300° 360° H

Fig. 24. A graphical representation of RGB coordinates given values for HSV. Chapter 8

Day 8

8.1 RGB color model

“RGB” redirects here. For other uses, see RGB (disambiguation). The RGB color model is an additive color model in which red, green and blue light are added together in various

A representation of additive color mixing. Projection of primary color lights on a white screen shows secondary colors where two overlap; the combination of all three of red, green and blue in equal intensities makes white. ways to reproduce a broad array of colors. The name of the model comes from the initials of the three additive primary colors, red, green and blue. The main purpose of the RGB color model is for the sensing, representation and display of images in electronic systems, such as televisions and computers, though it has also been used in conventional photography. Before the electronic age, the RGB color model already had a solid theory behind it, based in human perception of colors.

129 130 CHAPTER 8. DAY 8

RGB is a device-dependent color model: different devices detect or reproduce a given RGB value differently, since the color elements (such as phosphors or dyes) and their response to the individual R, G and B levels vary from manufacturer to manufacturer, or even in the same device over time. Thus an RGB value does not define the same color across devices without some kind of color management. Typical RGB input devices are color TV and video cameras, image scanners, video games, and digital cameras. Typical RGB output devices are TV sets of various technologies (CRT, LCD, plasma, OLED, Quantum-Dots etc.), computer and mobile phone displays, video projectors, multicolor LED displays and large screens such as JumboTron. Color printers, on the other hand are not RGB devices, but subtractive color devices (typically CMYK color model). This article discusses concepts common to all the different color spaces that use the RGB color model, which are used in one implementation or another in color image-producing technology.

8.1.1 Additive primary colors

Additive color mixing: adding red to green yields yellow; adding red to blue yields magenta; adding green to blue yields cyan; adding all three primary colors together yields white.

To form a color with RGB, three light beams (one red, one green and one blue) must be superimposed (for example by emission from a black screen or by reﬂection from a white screen). Each of the three beams is called a component of that color, and each of them can have an arbitrary intensity, from fully oﬀ to fully on, in the mixture. 8.1. RGB COLOR MODEL 131

The RGB color model is additive in the sense that the three light beams are added together, and their light spectra add, wavelength for wavelength, to make the final color’s spectrum.[1][2] Zero intensity for each component gives the darkest color (no light, considered the black), and full intensity of each gives a white; the quality of this white depends on the nature of the primary light sources, but if they are properly balanced, the result is a neutral white matching the system’s white point. When the intensities for all the components are the same, the result is a shade of gray, darker or lighter depending on the intensity. When the intensities are different, the result is a colorized hue, more or less saturated depending on the difference of the strongest and weakest of the intensities of the primary colors employed. When one of the components has the strongest intensity, the color is a hue near this primary color (reddish, greenish or bluish), and when two components have the same strongest intensity, then the color is a hue of a secondary color (a shade of cyan, magenta or yellow). A secondary color is formed by the sum of two primary colors of equal intensity: cyan is green+blue, magenta is red+blue, and yellow is red+green. Every secondary color is the complement of one primary color; when a primary and its complementary secondary color are added together, the result is white: cyan complements red, magenta complements green, and yellow complements blue. The RGB color model itself does not define what is meant by red, green and blue colorimetrically, and so the results of mixing them are not specified as absolute, but relative to the primary colors. When the exact chromaticities of the red, green and blue primaries are defined, the color model then becomes an absolute color space, such as sRGB or Adobe RGB; see RGB color spaces for more details.

8.1.2 Physical principles for the choice of red, green and blue

The choice of primary colors is related to the physiology of the human eye; good primaries are stimuli that maximize the difference between the responses of the cone cells of the human retina to light of different wavelengths, and that thereby make a large color triangle.[3] The normal three kinds of light-sensitive photoreceptor cells in the human eye (cone cells) respond most to yellow (long wavelength or L), green (medium or M), and violet (short or S) light (peak wavelengths near 570 nm, 540 nm and 440 nm, respectively[3]). The difference in the signals received from the three kinds allows the brain to differentiate a wide gamut of different colors, while being most sensitive (overall) to yellowish-green light and to differences between hues in the green-to-orange region. As an example, suppose that light in the orange range of wavelengths (approximately 577 nm to 597 nm) enters the eye and strikes the retina. Light of these wavelengths would activate both the medium and long wavelength cones of the retina, but not equally—the long-wavelength cells will respond more. The difference in the response can be detected by the brain, and this difference is the basis of our perception of orange. Thus, the orange appearance of an object results from light from the object entering our eye and stimulating the different cones simultaneously but to different degrees. Use of the three primary colors is not sufficient to reproduce all colors; only colors within the color triangle defined by the chromaticities of the primaries can be reproduced by additive mixing of non-negative amounts of those colors of light.[3]

8.1.3 History of RGB color model theory and usage

The RGB color model is based on the Young–Helmholtz theory of trichromatic color vision, developed by Thomas Young and Hermann Helmholtz in the early to mid nineteenth century, and on James Clerk Maxwell's color triangle that elaborated that theory (circa 1860). Early color photographs 132 CHAPTER 8. DAY 8

A set of primary colors, such as the sRGB primaries, deﬁne a color triangle; only colors within this triangle can be reproduced by mixing the primary colors. Colors outside the color triangle are therefore shown here as gray. The primaries and the D65 white point of sRGB are shown.

The ﬁrst permanent color photograph, taken by J.C. Maxwell in 8.1. RGB COLOR MODEL 133

1861 using three ﬁlters, speciﬁcally red, green, and violet-blue.

A photograph of Mohammed Alim Khan (1880– 1944), Emir of Bukhara, taken in 1911 by Sergei Mikhailovich Prokudin-Gorskii using three exposures with blue, green, and red ﬁlters.

Photography

The first experiments with RGB in early color photography were made in 1861 by Maxwell himself, and involved the process of combining three color-filtered separate takes.[4] To reproduce the color photograph, three matching projections over a screen in a dark room were necessary. The additive RGB model and variants such as orange–green–violet were also used in the Autochrome Lumière color plates and other screen-plate technologies such as the Joly color screen and the Paget process in the early twentieth century. Color photography by taking three separate plates was used by other pioneers, such as the Russian Sergey Prokudin-Gorsky in the period 1909 through 1915.[5] Such methods lasted until about 1960 using the expensive and extremely complex tri-color carbro Autotype process.[6] When employed, the reproduction of prints from three-plate photos was done by dyes or pigments using the complementary CMY model, by simply using the negative plates of the filtered takes: reverse red gives the cyan plate, and so on.

Television

Before the development of practical electronic TV, there were patents on mechanically scanned color systems as early as 1889 in Russia. The color TV pioneer John Logie Baird demonstrated the world’s first RGB color transmission in 1928, and also the world’s first color broadcast in 1938, in London. In his experiments, scanning and display were done mechanically by spinning colorized wheels.[7][8] The Columbia Broadcasting System (CBS) began an experimental RGB field-sequential color system in 1940. Images were scanned electrically, but the system still used a moving part: the transparent RGB color wheel rotating at above 1,200 rpm in synchronism with the vertical scan. The camera and the cathode-ray tube (CRT) were both monochromatic. Color was provided by color wheels in the camera and the receiver.[9][10][11] More recently, color wheels have been used in field-sequential projection TV receivers based on the Texas Instruments monochrome DLP imager. The modern RGB shadow mask technology for color CRT displays was patented by Werner Flechsig in Germany in 1938.[12]

Personal computers

Early personal computers of the late 1970s and early 1980s, such as those from Apple, Atari and Commodore, did not use RGB as their main method to manage colors, but rather composite video. IBM introduced a 16-color scheme (four bits—one bit each for red, green, blue, and intensity) with the Color Graphics Adapter (CGA) for its ﬁrst IBM PC (1981), later improved with the Enhanced Graphics Adapter (EGA) in 1984. The ﬁrst manufacturer of a truecolor graphic card for PCs (the TARGA) was Truevision in 1987, but it was not until the arrival of the Video 134 CHAPTER 8. DAY 8

Graphics Array (VGA) in 1987 that RGB became popular, mainly due to the analog signals in the connection between the adapter and the monitor which allowed a very wide range of RGB colors. Actually, it had to wait a few more years because the original VGA cards were palette-driven just like EGA, although with more freedom than VGA, but because the VGA connectors were analogue, later variants of VGA (made by various manufacturers under the informal name Super VGA) eventually added truecolor. In 1992, magazines heavily advertised truecolor Super VGA hardware.

8.1.4 RGB devices

RGB and displays

Cutaway rendering of a color CRT: 1. Electron guns 2. Electron beams 3. Focusing coils 4. Deﬂection coils 5. Anode connection 6. Mask for separating beams for red, green, and blue part of displayed image 7. Phosphor layer with red, green, and blue zones 8. Close-up of the phosphor-coated inner side of the screen

One common application of the RGB color model is the display of colors on a cathode ray tube (CRT), liquid crystal display (LCD), plasma display, or organic light emitting diode (OLED) display such as a television, a computer’s monitor, or a large scale screen. Each pixel on the screen is built by driving three small and very close but still separated RGB light sources. At common viewing distance, the separate sources are indistinguishable, which tricks the eye to see a given solid color. All the pixels together arranged in the rectangular screen surface conforms the color image. During digital image processing each pixel can be represented in the computer memory or interface hardware (for example, a graphics card) as binary values for the red, green, and blue color components. When properly managed, these values are converted into intensities or voltages via gamma correction to correct the inherent nonlinearity of some devices, such that the intended intensities are reproduced on the display. The Quattron released by Sharp uses RGB color and adds yellow as a sub-pixel, supposedly allowing an increase in the number of available colors. 8.1. RGB COLOR MODEL 135

Color wheel with RGB pixels of the colors

Video electronics RGB is also the term referring to a type of component video signal used in the video electronics industry. It consists of three signals—red, green and blue—carried on three separate cables/pins. RGB signal formats are often based on modiﬁed versions of the RS-170 and RS-343 standards for monochrome video. This type of video signal is widely used in Europe since it is the best quality signal that can be carried on the standard SCART connector. This signal is known as RGBS (4 BNC/RCA terminated cables exist as well), but it is directly compatible with RGBHV used for computer monitors (usually carried on 15-pin cables terminated with 15-pin D-sub or 5 BNC connectors), which carries separate horizontal and vertical sync signals. Outside Europe, RGB is not very popular as a video signal format; S-Video takes that spot in most non-European regions. However, almost all computer monitors around the world use RGB.

Video framebuffer A framebuffer is a digital device for computers which stores data in the so-called video memory (comprising an array of Video RAM or similar chips). This data goes either to three digital-to-analog converters (DACs) (for analog monitors), one per primary color, or directly to digital monitors. Driven by software, the CPU (or other specialized chips) write the appropriate bytes into the video memory to define the image. Modern systems encode pixel color values by devoting eight bits to each of the R, G and B components. RGB information can be either carried directly by the pixel bits themselves or provided by a separate color look-up table (CLUT) if indexed color graphic modes are used. 136 CHAPTER 8. DAY 8

RGB phosphor dots in a CRT monitor

A CLUT is a specialized RAM that stores R, G and B values that define specific colors. Each color has its own address (index)—consider it as a descriptive reference number that provides that specific color when the image needs it. The content of the CLUT is much like a palette of colors. Image data that uses indexed color specifies addresses within the CLUT to provide the required R, G and B values for each specific pixel, one pixel at a time. Of course, before displaying, the CLUT has to be loaded with R, G and B values that define the palette of colors required for each image to be rendered. Some video applications store such palettes in PAL files (Microsoft AOE game, for example uses over half-a-dozen[13]) and can combine CLUTs on screen.

RGB24 and RGB32

This indirect scheme restricts the number of available colors in an image CLUT —typically 256-cubed (8 bits in three color channels with values of 0–255)— although each color in the RGB24 CLUT table has only 8 bits representing 256 codes for each of the R, G and B primaries combinatorial math theory says this means that any given color can be one of 16,777,216 possible colors. However, the advantage is that an indexed-color image file can be significantly smaller than it would be with only 8 bits per pixel for each primary. Modern storage, however, is far less costly, greatly reducing the need to minimize image file size. By using an appropriate combination of red, green and blue intensities, many colors can be displayed. Current typical display adapters use up to 24-bits of information for each pixel: 8-bit per component multiplied by three components (see the Digital representations section below (24bits = 2563, each primary value of 8 bits with values of 0–255). With this system, 16,777,216 (2563 or 224) discrete combinations of R, G and B values are allowed, providing millions of different (though not necessarily distinguishable) hue, saturation and lightness shades. Increased shading has been implemented in various ways, some formats such as .png and .tga files among others using a fourth greyscale color channel as a masking layer, often called RGB32. For images with a modest range of brightnesses from the darkest to the lightest, eight bits per primary color provides good-quality images, but extreme images require more bits per primary color as well as advanced display technology. For more information see High Dynamic Range (HDR) imaging. 8.1. RGB COLOR MODEL 137

RGB sub-pixels in an LCD TV (on the right: an orange and a blue color; on the left: a close-up)

Nonlinearity Main article: Gamma correction

In classic cathode ray tube (CRT) devices, the brightness of a given point over the fluorescent screen due to the impact of accelerated electrons is not proportional to the voltages applied to the electron gun control grids, but to an expansive function of that voltage. The amount of this deviation is known as its gamma value ( γ ), the argument for a power law function, which closely describes this behavior. A linear response is given by a gamma value of 1.0, but actual CRT nonlinearities have a gamma value around 2.0 to 2.5. Similarly, the intensity of the output on TV and computer display devices is not directly proportional to the R, G and B applied electric signals (or file data values which drive them through Digital-to-Analog Converters). On a typical standard 2.2-gamma CRT display, an input intensity RGB value of (0.5, 0.5, 0.5) only outputs about 22% of full brightness (1.0, 1.0, 1.0), instead of 50%.[14] To obtain the correct response, a gamma correction is used in encoding the image data, and possibly further corrections as part of the color calibration process of the device. Gamma affects black-and-white TV as well as color. In standard color TV, broadcast signals are gamma corrected.

RGB and cameras

In color television and video cameras manufactured before the 1990s, the incoming light was separated by prisms and ﬁlters into the three RGB primary colors feeding each color into a separate video camera tube (or pickup tube). These tubes are a type of cathode ray tube, not to be confused with that of CRT displays. With the arrival of commercially viable charge-coupled device (CCD) technology in the 1980s, ﬁrst the pickup tubes were replaced with this kind of sensor. Later, higher scale integration electronics was applied (mainly by Sony), simplifying and even removing the intermediate optics, thereby reducing the size of home video cameras and eventually leading to the development of full camcorders. Current webcams and mobile phones with cameras are the most miniaturized commercial forms of such technology. 138 CHAPTER 8. DAY 8

The Bayer ﬁlter arrangement of color ﬁlters on the pixel array of a digital image sensor

Photographic digital cameras that use a CMOS or CCD image sensor often operate with some variation of the RGB model. In a Bayer ﬁlter arrangement, green is given twice as many detectors as red and blue (ratio 1:2:1) in order to achieve higher luminance resolution than chrominance resolution. The sensor has a grid of red, green and blue detectors arranged so that the ﬁrst row is RGRGRGRG, the next is GBGBGBGB, and that sequence is repeated in subsequent rows. For every channel, missing pixels are obtained by interpolation in the demosaicing process to build up the complete image. Also, other processes used to be applied in order to map the camera RGB measurements into a standard RGB color space as sRGB.

RGB and scanners

In computing, an image scanner is a device that optically scans images (printed text, handwriting, or an object) and converts it to a digital image which is transferred to a computer. Among other formats, flat, drum and film scanners exist, and most of them support RGB color. They can be considered the successors of early telephotography input devices, which were able to send consecutive scan lines as analog amplitude modulation signals through standard telephonic lines to appropriate receivers; such systems were in use in press since the 1920s to the mid-1990s. Color telephotographs were sent as three separated RGB filtered images consecutively. Currently available scanners typically use charge-coupled device (CCD) or contact image sensor (CIS) as the image sensor, whereas older drum scanners use a photomultiplier tube as the image sensor. Early color film scanners used a halogen lamp and a three-color filter wheel, so three exposures were needed to scan a single color image. Due to heating problems, the worst of them being the potential destruction of the scanned film, this technology was later replaced by non-heating light sources such as color LEDs.

8.1.5 Numeric representations

A color in the RGB color model is described by indicating how much of each of the red, green, and blue is included. The color is expressed as an RGB triplet (r,g,b), each component of which can vary from zero to a defined maximum value. If all the components are at zero the result is black; if all are at maximum, the result is the brightest representable white. These ranges may be quantified in several different ways: 8.1. RGB COLOR MODEL 139

R: 213 G: 111 B: 56

A typical RGB color selector in graphic software. Each slider ranges from 0 to 255.

Hexadecimal 8-bit RGB representations of the main 125 colors

• From 0 to 1, with any fractional value in between. This representation is used in theoretical analyses, and in systems that use ﬂoating point representations.

• Each color component value can also be written as a percentage, from 0% to 100%.

• In computers, the component values are often stored as integer numbers in the range 0 to 255, the range that a single 8-bit byte can oﬀer. These are often represented as either decimal or hexadecimal numbers.

• High-end digital image equipment are often able to deal with larger integer ranges for each primary color, such 140 CHAPTER 8. DAY 8

as 0..1023 (10 bits), 0..65535 (16 bits) or even larger, by extending the 24-bits (three 8-bit values) to 32-bit, 48-bit, or 64-bit units (more or less independent from the particular computer’s word size).

For example, brightest saturated red is written in the diﬀerent RGB notations as:

In many environments, the component values within the ranges are not managed as linear (that is, the numbers are nonlinearly related to the intensities that they represent), as in digital cameras and TV broadcasting and receiving due to gamma correction, for example.[15] Linear and nonlinear transformations are often dealt with via digital image processing. Representations with only 8 bits per component are considered suﬃcient if gamma encoding is used.[16] Following is the mathematical relationship between RGB space to HSI space (hue, saturation, and intensity: HSI color space): R + G + B I = 3 3 S = 1 − min(R, G, B) (R + G + B) ( ) 1 1 ((R − G) + (R − B)) 2 H = cos−1 2 (R − G)2 + (R − B)(G − B)

Color depth

Main article: Color depth

The RGB color model is one of the most common ways to encode color in computing, and several diﬀerent binary digital representations are in use. The main characteristic of all of them is the quantization of the possible values per component (technically a Sample (signal) ) by using only integer numbers within some range, usually from 0 to some power of two minus one (2n – 1) to ﬁt them into some bit groupings. Encodings of 1, 2, 4, 5, 8 and 16 bits per color are commonly found; the total number of bits used for an RGB color is typically called the color depth.

8.1.6 Geometric representation

See also RGB color space

Since colors are usually deﬁned by three components, not only in the RGB model, but also in other color models such as CIELAB and Y'UV, among others, then a three-dimensional volume is described by treating the component values as ordinary cartesian coordinates in a euclidean space. For the RGB model, this is represented by a cube using non-negative values within a 0–1 range, assigning black to the origin at the vertex (0, 0, 0), and with increasing intensity values running along the three axes up to white at the vertex (1, 1, 1), diagonally opposite black. An RGB triplet (r,g,b) represents the three-dimensional coordinate of the point of the given color within the cube or its faces or along its edges. This approach allows computations of the color similarity of two given RGB colors by simply calculating the distance between them: the shorter the distance, the higher the similarity. Out-of-gamut computations can also be performed this way.

8.1.7 Colors in web-page design

Main article: Web colors

The RGB color model for HTML was formally adopted as an Internet standard in HTML 3.2, though it had been in use for some time before that. Initially, the limited color depth of most video hardware led to a limited color palette of 216 RGB colors, deﬁned by the Netscape Color Cube. With the predominance of 24-bit displays, the use of the full 16.7 million colors of the HTML RGB color code no longer poses problems for most viewers. 8.1. RGB COLOR MODEL 141

The RGB color model mapped to a cube. The horizontal x-axis as red values increasing to the left, y-axis as blue increasing to the lower right and the vertical z-axis as green increasing towards the top. The origin, black is the vertex hidden from view.

The web-safe color palette consists of the 216 (63) combinations of red, green, and blue where each color can take one of six values (in hexadecimal): #00, #33, #66, #99, #CC or #FF (based on the 0 to 255 range for each value discussed above). These hexadecimal values = 0, 51, 102, 153, 204, 255 in decimal, which = 0%, 20%, 40%, 60%, 80%, 100% in terms of intensity. This seems ﬁne for splitting up 216 colors into a cube of dimension 6. However, lacking gamma correction, the perceived intensity on a standard 2.5 gamma CRT / LCD is only: 0%, 2%, 10%, 28%, 57%, 100%. See the actual web safe color palette for a visual conﬁrmation that the majority of the colors produced are very dark or see Xona.com Color List for a side-by-side comparison of proper colors next to their equivalent lacking proper gamma correction. The syntax in CSS is: rgb(#,#,#) where # equals the proportion of red, green and blue respectively. This syntax can be used after such selectors as “background-color:" or (for text) “color:".

8.1.8 Color management

Main article: Color management

Proper reproduction of colors, especially in professional environments, requires color management of all the devices involved in the production process, many of them using RGB. Color management results in several transparent conversions between device-independent and device-dependent color spaces (RGB and others, as CMYK for color printing) during a typical production cycle, in order to ensure color consistency throughout the process. Along with the creative processing, such interventions on digital images can damage the color accuracy and image detail, especially where the gamut is reduced. Professional digital devices and software tools allow for 48 bpp (bits per pixel) images to be manipulated (16 bits per channel), to minimize any such damage. 142 CHAPTER 8. DAY 8

ICC-compliant applications, such as Adobe Photoshop, use either the Lab color space or the CIE 1931 color space as a Proﬁle Connection Space when translating between color spaces.[17]

8.1.9 RGB model and luminance–chrominance formats relationship

All luminance–chrominance formats used in the different TV and video standards such as YIQ for NTSC, YUV for PAL, YDBDR for SECAM, and YPBPR for component video use color difference signals, by which RGB color images can be encoded for broadcasting/recording and later decoded into RGB again to display them. These intermediate formats were needed for compatibility with pre-existent black-and-white TV formats. Also, those color difference signals need lower data bandwidth compared to full RGB signals. Similarly, current high-efficiency digital color image data compression schemes such as JPEG and MPEG store RGB color internally in YCBCR format, a digital luminance-chrominance format based on YPBPR. The use of YCBCR also allows to perform lossy subsampling with the chroma channels (typically to 4:2:2 or 4:1:1 ratios), which it aids to reduce the resultant file size.

8.1.10 See also

• Color theory • Colour banding • List of color palettes • RG color space • RGBA color space

8.1.11 References

[1] Charles A. Poynton (2003). Digital Video and HDTV: Algorithms and Interfaces. Morgan Kaufmann. ISBN 1-55860-792- 7. [2] Nicholas Boughen (2003). Lightwave 3d 7.5 Lighting. Wordware Publishing, Inc. ISBN 1-55622-354-4. [3] R. W. G. Hunt (2004). The Reproduction of Colour (6th ed.). Chichester UK: Wiley–IS&T Series in Imaging Science and Technology. ISBN 0-470-02425-9. [4] Robert Hirsch (2004). Exploring Colour Photography: A Complete Guide. Laurence King Publishing. ISBN 1-85669-420- 8. [5] Photographer to the Tsar: Sergei Mikhailovich Prokudin-Gorskii Library of Congress. [6] “The Evolution of Color Pigment Printing”. Artfacts.org. Retrieved 2013-04-29. [7] John Logie Baird, Television Apparatus and the Like, U.S. patent, ﬁled in U.K. in 1928. [8] Baird Television: Crystal Palace Television Studios. Previous color television demonstrations in the U.K. and U.S. had been via closed circuit. [9] “Color Television Success in Test”. NY Times. 1940-08-30. p. 21. Retrieved 2008-05-12. [10] "CBS Demonstrates Full Color Television,” Wall Street Journal, Sept. 5, 1940, p. 1. [11] “Television Hearing Set”. NY Times. 1940-11-13. p. 26. Retrieved 2008-05-12. [12] Morton, David L. (1999). “Television Broadcasting”. A History of Electronic Entertainment Since 1945 (PDF). IEEE. ISBN 0-7803-9936-6. Archived from the original (PDF) on March 6, 2009. [13] By directory search [14] Steve Wright (2006). Digital Compositing for Film and Video. Focal Press. ISBN 0-240-80760-X. [15] Edwin Paul J. Tozer (2004). Broadcast Engineer’s Reference Book. Elsevier. ISBN 0-240-51908-6. [16] John Watkinson (2008). The art of digital video. Focal Press. p. 272. ISBN 978-0-240-52005-6. [17] ICC. “Why Color Management?" (PDF). Retrieved 2008-04-16. The two PCS’s in the ICC system are CIE-XYZ and CIELAB 8.2. CMYK COLOR MODEL 143

8.1.12 External links

• HEX to RGB conversion • RGB to HEX conversion • Demonstrative color conversion applet • RGB color codes

8.2 CMYK color model

“CMYK” redirects here. For the extended play by James Blake, see CMYK (EP). “CMYB” redirects here. For the cMyb gene, see MYB (gene).

The CMYK color model (process color, four color) is a subtractive color model, used in color printing, and is also used to describe the printing process itself. CMYK refers to the four inks used in some color printing: cyan, magenta, yellow and key (black). Though it varies by print house, press operator, press manufacturer, and press run, ink is typically applied in the order of the abbreviation. The “K” in CMYK stands for key because in four-color printing, cyan, magenta and yellow printing plates are carefully keyed, or aligned, with the key of the black key plate. Some sources suggest that the “K” in CMYK comes from the last letter in “black" and was chosen because B already means blue.[1][2] Some sources claim this explanation, although useful as a mnemonic, is incorrect, that K comes only from “Key” because black is often used as outline and printed ﬁrst.[3] The CMYK model works by partially or entirely masking colors on a lighter, usually white, background. The ink reduces the light that would otherwise be reﬂected. Such a model is called subtractive because inks “subtract” brightness from white. In additive color models such as RGB, white is the “additive” combination of all primary colored lights, while black is the absence of light. In the CMYK model, it is the opposite: white is the natural color of the paper or other background, while black results from a full combination of colored inks. To save cost on ink, and to produce deeper black tones, unsaturated and dark colors are produced by using black ink instead of the combination of cyan, magenta and yellow.

8.2.1 Halftoning

Main article: Halftone

With CMYK printing, halftoning (also called screening) allows for less than full saturation of the primary colors; tiny dots of each primary color are printed in a pattern small enough that human beings perceive a solid color. Magenta printed with a 20% halftone, for example, produces a pink color, because the eye perceives the tiny magenta dots on the large white paper as lighter and less saturated than the color of pure magenta ink. Without halftoning, the three primary process colors could be printed only as solid blocks of color, and therefore could produce only seven colors: the three primaries themselves, plus three secondary colors produced by layering two of the primaries: cyan and yellow produce green, cyan and magenta produce blue, yellow and magenta produce red (these subtractive secondary colors correspond roughly to the additive primary colors) plus layering all three of them resulting in black. With halftoning, a full continuous range of colors can be produced.

Screen angle

Main article: Screen angle

To improve print quality and reduce moiré patterns, the screen for each color is set at a diﬀerent angle. While the angles depend on how many colors are used and the preference of the press operator, typical CMYK process printing uses any of the following screen angles:[4][5] 144 CHAPTER 8. DAY 8

This diagram shows three examples of color halftoning with CMYK separations, as well as the combined halftone pattern and how the human eye would observe the combined halftone pattern from a suﬃcient distance.

8.2.2 Beneﬁts of using black ink

The “black” generated by mixing commercially practical cyan, magenta and yellow inks is unsatisfactory, so four-color printing uses black ink in addition to the subtractive primaries. Common reasons for using black ink include:[6]

• In traditional preparation of color separations, a red keyline on the black line art marked the outline of solid or tint color areas. In some cases a black keyline was used when it served as both a color indicator and an outline to be printed in black. Because usually the black plate contained the keyline, the K in CMYK represents the keyline or black plate, also sometimes called the key plate.

• Text is typically printed in black and includes ﬁne detail (such as serifs), so to reproduce text or other ﬁnely detailed outlines, without slight blurring, using three inks would require impractically accurate registration.

• A combination of 100% cyan, magenta, and yellow inks soaks the paper with ink, making it slower to dry, causing bleeding, or (especially on cheap paper such as newsprint) weakening the paper so much that it tears.

• Although a combination of 100% cyan, magenta, and yellow inks should, in theory, completely absorb the entire visible spectrum of light and produce a perfect black, practical inks fall short of their ideal characteristics and the result is actually a dark muddy color that does not quite appear black. Adding black ink absorbs more light and yields much better blacks.

• Using black ink is less expensive than using the corresponding amounts of colored inks.

When a very dark area is desirable, a colored or gray CMY “bedding” is applied first, then a full black layer is applied on top, making a rich, deep black; this is called rich black.[7] A black made with just CMY inks is sometimes called a composite black. The amount of black to use to replace amounts of the other ink is variable, and the choice depends on the technology, paper and ink in use. Processes called under color removal, under color addition, and gray component replacement are used to decide on the final mix; different CMYK recipes will be used depending on the printing task. 8.2. CMYK COLOR MODEL 145

75° 105° 90° 75° 45°

15° 15° 0°

75° 105°90° 45° 45° 15° 165° 0°

Typical halftone screen angles.

8.2.3 Other printer color models

CMYK or process color printing is contrasted with spot color printing, in which specific colored inks are used to generate the colors appearing on paper. Some printing presses are capable of printing with both four-color process inks and additional spot color inks at the same time. High-quality printed materials, such as marketing brochures and books, may include photographs requiring process-color printing, other graphic effects requiring spot colors (such as metallic inks), and finishes such as varnish, which enhances the glossy appearance of the printed piece. CMYK are the process printers which often have a relatively small color gamut. Processes such as Pantone's proprietary six-color (CMYKOG) Hexachrome considerably expand the gamut. Light, saturated colors often cannot be created with CMYK, and light colors in general may make visible the halftone pattern. Using a CcMmYK process, with the addition of light cyan and magenta inks to CMYK, can solve these problems, and such a process is used by many inkjet printers, including desktop models.[8]

8.2.4 Comparison with RGB displays

Comparisons between RGB displays and CMYK prints can be difficult, since the color reproduction technologies and properties are very different. A computer monitor mixes shades of red, green, and blue light to create color pictures. A CMYK printer instead uses light-absorbing cyan, magenta and yellow inks, whose colors are mixed using dithering, halftoning, or some other optical technique. Similar to monitors, the inks used in printing produce a color gamut that is “only a subset of the visible spectrum” although both color modes have their own specific ranges. As a result of this items which are displayed on a computer monitor may not completely match the look of items which are printed if opposite color modes are being combined in both mediums.[9] When designing items to be printed, designers view the colors which they are choosing on an RGB color mode (their computer screen), and it is often difficult to visualize the way in which the color will turn out post printing because of this. 146 CHAPTER 8. DAY 8

A color photograph of the Teton Range.

Spectrum of Printed Paper

To reproduce color the CMYK color model codes for absorbing light rather than emitting it (as is assumed by RGB). The 'K' component absorbs all wavelengths and is therefore achromatic. The Cyan, Magenta and Yellow components are used for color reproduction and they may be viewed as the inverse of RGB. Cyan absorbs Red, Magenta absorbs Green and Yellow absorbs Blue (-R,-G,-B).

8.2.5 Conversion

Since RGB and CMYK spaces are both device-dependent spaces, there is no simple or general conversion formula that converts between them. Conversions are generally done through color management systems, using color profiles that describe the spaces being converted. Nevertheless, the conversions cannot be exact, particularly where these spaces have different gamuts. The problem of computing a colorimetric estimate of the color that results from printing various combinations of ink has been addressed by many scientists.[10] A general method that has emerged for the case of halftone printing is to treat each tiny overlap of color dots as one of 8 (combinations of CMY) or of 16 (combinations of CMYK) colors, which in this context are known as Neugebauer primaries. The resultant color would be an area-weighted colorimetric combination of these primary colors, except that the Yule–Nielsen effect ("dot gain") of scattered light between and within the areas complicates the physics and the analysis; empirical formulas for such analysis have been developed, in terms of detailed dye combination absorption spectra and empirical parameters.[10]

8.2.6 See also

• CcMmYK color model

• Grey component replacement 8.2. CMYK COLOR MODEL 147

0.9 520 ProPhoto RGB

0.8 540 Adobe RGB 1998 0.7 560 Colormatch RGB 0.6 sRGB SWOP CMYK 500 0.5 580 y 0.4 600 D65 white point 620 0.3

0.2

480 0.1

0.0 460 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 x

Comparison of some RGB and CMYK color gamut on a CIE 1931 xy chromaticity diagram.

• Jacob Christoph Le Blon • SWOP CMYK standard

8.2.7 Notes and references

[1] Galer, Mark; Horvat, Les (2003). Digital Imaging: Essential Skills. Focal Press. p. 74. ISBN 978-0-240-51913-5.

[2] Jennings, Simon (2003). Artist’s Color Manual: The Complete Guide to Working with Color. Chronicle Books LLC. p. 21. ISBN 978-0-8118-4143-6.

[3] Gatter, Mark (2004). Getting It Right in Print: Digital Pre-press for Graphic Designers. Laurence King Publishing. p. 31. ISBN 978-1-85669-421-6.

[4] Campbell, Alastair. The Designer’s Lexicon. 2000 Chronicle, San Francisco. p 192

[5] McCue, Claudia. Real World Print Production. 2007 Peachpit, Berkeley. p 31.

[6] Roger Pring (2000). WWW.Color. Watson–Guptill. ISBN 0-8230-5857-3. 148 CHAPTER 8. DAY 8

100

90

80

70

r 60 w e p o 50

40 pectral s

30

20

10

0 350 400 450 500 550 600 650 700 white SCA Graphosilk yellow SCA Graphosilk Wavelength (nm) yellow-orange SCA Graphosilk (70gsm) light orange SCA Graphosilk (70gsm) orange SCA Graphosilk (70gsm) red-orange SCA Graphosilk (70gsm) red SCA Graphosilk blue SCA Graphosilk green SCA Graphosilk (70gsm) White Orchid flower Yellow Rose red cyclamen flower Red Rose petal

Spectrum of the visible wavelengths on printed paper (SCA Graphosilk). Shown is the transition from Red to Yellow. White, red, blue and green are shown for reference. Readings from a white orchid flower, a rose (red and yellow petals), and a red cyclamen flower are shown for comparison. The units of spectral power are simply raw sensor values (with a linear response at specific wavelengths).

[7] R. S. Hodges (2003). The Guild Handbook of Scientiﬁc Illustration. John Wiley and Sons. ISBN 0-471-36011-2.

[8] Carla Rose (2003). Sams Teach Yourself Adobe Photoshop Elements 2 in 24 Hours. Sams Publishing. ISBN 0-672-32430- X.

[9] Damien van Holten, print international.org, “RGB Vs CMYK” http://www.printernational.org/rgb-versus-cmyk.php

[10] Gaurav Sharma (2003). Digital Color Imaging Handbook. CRC Press. ISBN 0-8493-0900-X.

8.2.8 External links

• XCmyk—CMYK to RGB Calculator with source code • Color Space Fundamentals—animated illustration of RGB vs. CMYK 8.2. CMYK COLOR MODEL 149

Early representation of the three color process, from 1902. Chapter 9

Day 9

9.1 Colorfulness

Original image, with relatively muted colors

L*C*h (CIELAB) chroma increased 50%

HSL saturation increased 50%; notice that changing HSL saturation also aﬀects the perceived lightness of a color

CIELAB lightness preserved, with a* and b* stripped, to make a grayscale image

150 9.1. COLORFULNESS 151

Colorfulness or saturation in colorimetry and color theory refers to the perceived intensity of a specific color. Colorfulness is the visual sensation according to which the perceived color of an area appears to be more or less chromatic.[1] Chroma is the colorfulness relative to the brightness of a similarly illuminated area that appears to be white or highly transmitting. Therefore, chroma should not be confused with colorfulness.[2] Saturation is the colorfulness of a color relative to its own brightness.[3] Though the general concept is intuitive, terms such as chroma, saturation, purity, and intensity are often used without great precision, and even when well-defined depend greatly on the specific color model in use. A highly colorful stimulus is vivid and intense, while a less colorful stimulus appears more muted, closer to gray. With no colorfulness at all, a color is a “neutral” gray (an image with no colorfulness in any of its colors is called grayscale). Any color can be described using three color appearance parameters — colorfulness (or chroma or saturation), lightness (or brightness), and hue .

9.1.1 Saturation

Saturation is one of three coordinates in the HSL and HSV color spaces. The saturation of a color is determined by a combination of light intensity and how much it is distributed across the spectrum of diﬀerent wavelengths. The purest (most saturated) color is achieved by using just one wavelength at a high intensity, such as in laser light. If the intensity drops, then as a result the saturation drops. To desaturate a color of given intensity in a subtractive system (such as watercolor), one can add white, black, gray, or the hue’s complement. Various correlates of saturation follow.

CIELUV The chroma normalized by the lightness:

C∗ √ s = uv = 13 (u′ − u′ )2 + (v′ − v′ )2 uv L∗ n n where (u′n, v′n) is the chromaticity of the white point, and chroma is deﬁned below.[4] By analogy, in CIELAB this would yield:

√ C∗ a∗2 + b∗2 s = ab = ab L∗ L∗ The CIE has not formally recommended this equation since CIELAB has no chromaticity diagram, and this definition therefore lacks direct correlation with older concepts of saturation.[5] Nevertheless, this equation provides a reasonable predictor of saturation, and demonstrates that adjusting the lightness in CIELAB while holding (a*, b*) fixed does affect the saturation. But the following formula is in agreement with the human perception of saturation: The formula proposed by Eva Lübbe is in agreement with the verbal definition of Manfred Richter: Saturation is the proportion of pure chromatic color in the total color sensation.[6]

∗ Cab Sab = √ 100% ∗ 2 ∗2 Cab + L where Sab is the saturation, L* the lightness and C*ab is the chroma of the color.

CIECAM02 The square root of the colorfulness divided by the brightness: √ s = M/Q This definition is inspired by experimental work done with the intention of remedying CIECAM97s's poor performance.[7][8] M is proportional to the chroma C (M = CFL0.25), thus the CIECAM02 definition bears some similarity to the CIELUV definition. An important difference is that the CIECAM02 model accounts for the viewing conditions through the parameter FL.[7] 152 CHAPTER 9. DAY 9

Saturation scale (0% at bottom, corresponding to black and white). 9.1. COLORFULNESS 153

9.1.2 Excitation purity

0.9 520

0.8 540

0.7 560 0.6 500 0.5 580 y 0.4 600 White point 620 (xn,yn) 0.3 490 (x,y) 700

0.2 (xI,yI) 480 0.1 470 460 0.0 380 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 x

Excitation purity is the relative distance from the white point. Contours of constant purity can be found by shrinking the spectral locus about the white point. The points along the line segment have the same hue, with pe increasing from 0 to 1 between the white point and position on the spectral locus (position of the color on the horseshoe shape in the diagram) or (as at the saturated end of the line shown in the diagram) position on the line of purples.

The excitation purity (purity for short) of a stimulus is the diﬀerence from the illuminant’s white point to the furthest point on the chromaticity diagram with the same hue (dominant wavelength for monochromatic sources); using the CIE 1931 color space:[9]

√ 2 2 (x − xn) + (y − yn) pe = 2 2 (xI − xn) + (yI − yn) where (xn, yn) is the chromaticity of the white point and (xI, yI) is the point on the perimeter whose line segment to 154 CHAPTER 9. DAY 9

the white point contains the chromaticity of the stimulus. Diﬀerent color spaces, such as CIELAB or CIELUV may be used, and will yield diﬀerent results.

9.1.3 Chroma in CIE 1976 L*a*b* and L*u*v* color spaces

See also: Psychophysics

The naïve definition of saturation does not specify its response function. In the CIE XYZ and RGB color spaces, the saturation is defined in terms of additive color mixing, and has the property of being proportional to any scaling centered at white or the white point illuminant. However, both color spaces are nonlinear in terms of psychovisually perceived color differences. It is also possible—and sometimes desirable—to define a saturation-like quantity that is linearized in term of the psychovisual perception. In the CIE 1976 L*a*b* and L*u*v* color spaces, the unnormalized chroma is the radial component of the cylindrical coordinate CIE L*C*h (lightness, chroma, hue) representation of the L*a*b* and L*u*v* color spaces, also denoted as CIE L*C*h(a*b*) or CIE L*C*h for short, and CIE L*C*h(u*v*). The transformation of (a*, b*) to (C*ab, hab) is given by:

√ ∗ ∗2 ∗2 Cab = a + b b∗ h = arctan ab a∗ and analogously for CIE L*C*h(u*v*). The chroma in the CIE L*C*h(a*b*) and CIE L*C*h(u*v*) coordinates has the advantage of being more psychovisually linear, yet they are non-linear in terms of linear component color mixing. And therefore, chroma in CIE 1976 L*a*b* and L*u*v* color spaces is very much diﬀerent from the traditional sense of “saturation”.

Chroma in color appearance models

Another, psychovisually even more accurate, but also more complex method to obtain or specify the saturation is to use a color appearance model. Here, the chroma color appearance parameter might (depending on the color appearance model) be intertwined with e.g. the physical brightness of the illumination or the characteristics of the emitting/reﬂecting surface, which is more sensible psychovisually.

9.1.4 References

[1] Fairchild, Mark (2013). Color Appearance Models. John Wiley & Sons., page 87. [2] Colorfulness Vs. Chroma [3] Mark D. Fairchild. “Color Appearance Models: CIECAM02 and Beyond”. Slides from a tutorial at the IS&T/SID 12th Color Imaging Conference. 9 November 2004. Retrieved 19 September 2007. [4] Schanda, János (2007). Colorimetry: Understanding the CIE System. Wiley Interscience. ISBN 978-0-470-04904-4., page 88. [5] Hunt, Robert William Gainer (1993). Leslie D. Stroebel, Richard D. Zakia, ed. The Focal Encyclopedia of Photography. Focal Press. p. 124. ISBN 0-240-51417-3. [6] Lübbe, Eva (2010). Colours in the Mind - Colour Systems in Reality- A formula for colour saturation. [Book on Demand]. ISBN 978-3-7881-4057-1. [7] Moroney, Nathan; Fairchild, Mark D.; Hunt, Robert W.G.; Li, Changjun; Luo, M. Ronnier; Newman, Todd (November 12, 2002). IS&T/SID Tenth Color Imaging Conference. The CIECAM02 Color Appearance Model (PDF). Scottsdale, Arizona: The Society for Imaging Science and Technology. ISBN 0-89208-241-0. [8] Juan, Lu-Yin G.; Luo, Ming R. (June 2002). Robert Chung, Allan Rodrigues, eds. Magnitude estimation for scaling saturation. 9th Congress of the International Colour Association. Proceedings of SPIE. 4421. pp. 575–578. doi:10.1117/12.464511. [9] Stroebel, Leslie D.; Zakia, Richard D. (1993). The Focal Encyclopedia of Photography (3E ed.). Focal Press. p. 121. ISBN 0-240-51417-3. 9.2. GRAYSCALE 155

9.2 Grayscale

“Greyscale” redirects here. For the ﬁlm, see Greyscale (ﬁlm). Not to be confused with Gray code. For variations of the base color, see shades of gray.

In photography and computing, a grayscale or greyscale digital image is an image in which the value of each pixel is a single sample, that is, it carries only intensity information. Images of this sort, also known as black-and-white, are composed exclusively of shades of gray, varying from black at the weakest intensity to white at the strongest.[1] Grayscale images are distinct from one-bit bi-tonal black-and-white images, which in the context of computer imaging are images with only two colors, black and white (also called bilevel or binary images). Grayscale images have many shades of gray in between. Grayscale images are often the result of measuring the intensity of light at each pixel in a single band of the electromagnetic spectrum (e.g. infrared, visible light, ultraviolet, etc.), and in such cases they are monochromatic proper when only a given frequency is captured. But also they can be synthesized from a full color image; see the section about converting to grayscale.

9.2.1 Numerical representations

The intensity of a pixel is expressed within a given range between a minimum and a maximum, inclusive. This range is represented in an abstract way as a range from 0 (total absence, black) and 1 (total presence, white), with any fractional values in between. This notation is used in academic papers, but this does not define what “black” or “white” is in terms of colorimetry. Another convention is to employ percentages, so the scale is then from 0% to 100%. This is used for a more intuitive approach, but if only integer values are used, the range encompasses a total of only 101 intensities, which are insuffi- cient to represent a broad gradient of grays. Also, the percentile notation is used in printing to denote how much ink is employed in halftoning, but then the scale is reversed, being 0% the paper white (no ink) and 100% a solid black (full ink). In computing, although the grayscale can be computed through rational numbers, image pixels are stored in binary, quantized form. Some early grayscale monitors can only show up to sixteen (4-bit) different shades, but today grayscale images (as photographs) intended for visual display (both on screen and printed) are commonly stored with 8 bits per sampled pixel, which allows 256 different intensities (i.e., shades of gray) to be recorded, typically on a non-linear scale. The precision provided by this format is barely sufficient to avoid visible banding artifacts, but very convenient for programming because a single pixel then occupies a single byte. Technical uses (e.g. in medical imaging or remote sensing applications) often require more levels, to make full use of the sensor accuracy (typically 10 or 12 bits per sample) and to guard against roundoff errors in computations. Sixteen bits per sample (65,536 levels) is a convenient choice for such uses, as computers manage 16-bit words efficiently. The TIFF and the PNG (among other) image file formats support 16-bit grayscale natively, although browsers and many imaging programs tend to ignore the low order 8 bits of each pixel. No matter what pixel depth is used, the binary representations assume that 0 is black and the maximum value (255 at 8 bpp, 65,535 at 16 bpp, etc.) is white, if not otherwise noted.

9.2.2 Converting color to grayscale

Conversion of a color image to grayscale is not unique; different weighting of the color channels effectively represent the effect of shooting black-and-white film with different-colored photographic filters on the cameras.

Colorimetric (luminance-preserving) conversion to grayscale

A common strategy is to use the principles of photometry or, more broadly, colorimetry to match the luminance of the grayscale image to the luminance of the original color image.[2][3] This also ensures that both images will have the same absolute luminance, as can be measured in its SI units of candelas per square meter, in any given area of the image, given equal whitepoints. In addition, matching luminance provides matching perceptual lightness measures, 156 CHAPTER 9. DAY 9

A sample grayscale image.

such as L* (as in the 1976 CIE Lab color space) which is determined by the linear luminance Y (as in the CIE 1931 XYZ color space) which we will refer to here as Yᵢₑₐᵣ to avoid any ambiguity. To convert a color from a colorspace based on an RGB color model to a grayscale representation of its luminance, weighted sums must be calculated in a linear RGB space, that is, after the gamma compression function has been removed ﬁrst via gamma expansion.[4] For the sRGB color space, gamma expansion is deﬁned as 9.2. GRAYSCALE 157

  Csrgb , C ≤ 0.04045 (12.92 ) srgb Clinear = 2.4  Csrgb+0.055 1.055 ,Csrgb > 0.04045

where Cᵣ represents any of the three gamma-compressed sRGB primaries (Rᵣ, Gᵣ, and Bᵣ, each in range [0,1]) and Cᵢₑₐᵣ is the corresponding linear-intensity value (Rᵢₑₐᵣ, Gᵢₑₐᵣ, and Bᵢₑₐᵣ, also in range [0,1]). Then, linear luminance is calculated as a weighted sum of the three linear-intensity values. The sRGB color space is deﬁned in terms of the CIE 1931 linear luminance Yᵢₑₐᵣ, which is given by

[5] Ylinear = 0.2126Rlinear + 0.7152Glinear + 0.0722Blinear .

The coeﬃcients represent the measured intensity perception of typical trichromat humans, depending on the primaries being used; in particular, human vision is most sensitive to green and least sensitive to blue. To encode grayscale intensity in linear RGB, each of the three primaries can be set to equal the calculated linear luminance Y (replacing R,G,B by Y,Y,Y to get this linear grayscale). Linear luminance typically needs to be gamma compressed to get back to a conventional non-linear representation. For sRGB, each of its three primaries is then set to the same gamma- compressed Yᵣ given by the inverse of the gamma expansion above as

{ 12.92 Y , Y ≤ 0.0031308 Y = linear linear srgb 1/2.4 − 1.055 Ylinear 0.055,Ylinear > 0.0031308. In practice, because the three sRGB components are then equal, it is only necessary to store these values once in sRGB-compatible image formats that support a single-channel representation. Web browsers and other software that recognizes sRGB images will typically produce the same rendering for such a grayscale image as it would for an sRGB image having the same values in all three color channels.

Luma coding in video systems

Main article: luma (video)

For images in color spaces such as Y'UV and its relatives, which are used in standard color TV and video systems such as PAL, SECAM, and NTSC, a nonlinear luma component (Y') is calculated directly from gamma-compressed primary intensities as a weighted sum, which can be calculated quickly without the gamma expansion and compression used in colorimetric grayscale calculations. In the Y'UV and Y'IQ models used by PAL and NTSC, the rec601 luma (Y') component is computed as

Y ′ = 0.299R′ + 0.587G′ + 0.114B′

where we use the prime to distinguish these gamma-compressed values from the linear R, G, B, and Y discussed above. The ITU-R BT.709 standard used for HDTV developed by the ATSC uses diﬀerent color coeﬃcients, computing the luma component as

Y ′ = 0.2126R′ + 0.7152G′ + 0.0722B′

Although these are numerically the same coefficients used in sRGB above, the effect is different because here they are being applied directly to gamma-compressed values. Normally these colorspaces are transformed back to R'G'B' before rendering for viewing. To the extent that enough precision remains, they can then be rendered accurately. But if the luma component by itself is instead used directly as a grayscale representation of the color image, luminance is not preserved: two colors can have the same luma Y' but different CIE linear luminance Y (and thus different nonlinear Yᵣ as defined above) and therefore appear darker or lighter to a typical human than the original color. Similarly, two colors having the same luminance Y (and thus the same Yᵣ) will in general have different luma by either of the Y' luma definitions above.[6] 158 CHAPTER 9. DAY 9

9.2.3 Grayscale as single channels of multichannel color images

Color images are often built of several stacked color channels, each of them representing value levels of the given channel. For example, RGB images are composed of three independent channels for red, green and blue primary color components; CMYK images have four channels for cyan, magenta, yellow and black ink plates, etc. Here is an example of color channel splitting of a full RGB color image. The column at left shows the isolated color channels in natural colors, while at right there are their grayscale equivalences:

Composition of RGB from 3 Grayscale images

The reverse is also possible: to build a full color image from their separate grayscale channels. By mangling channels, using oﬀsets, rotating and other manipulations, artistic eﬀects can be achieved instead of accurately reproducing the original image.

9.2.4 See also

• Channel (digital image)

• Halftone

• False-color

• Sepia tone

• Cyanotype

• Morphological image processing

• Mezzotint

• List of monochrome and RGB palettes – Monochrome palettes section

• List of software palettes – Color gradient palettes and false color palettes sections 9.3. MIDDLE GRAY 159

• Achromatopsia, total color blindness, in which vision is limited to a grayscale.

• Zone System

9.2.5 References

[1] Stephen Johnson (2006). Stephen Johnson on Digital Photography. O'Reilly. ISBN 0-596-52370-X.

[2] Poynton, Charles A. “Rehabilitation of gamma.” Photonics West'98 Electronic Imaging. International Society for Optics and Photonics, 1998. online

[3] Charles Poynton, Constant Luminance

[4] Bruce Lindbloom, RGB Working Space Information (retrieved 2013-10-02)

[5] Michael Stokes, Matthew Anderson, Srinivasan Chandrasekar, and Ricardo Motta, “A Standard Default Color Space for the Internet - sRGB”, online see matrix at end of Part 2.

[6] Charles Poynton, The magnitude of nonconstant luminance errors in Charles Poynton, A Technical Introduction to Digital Video. New York: John WIley & Sons, 1996.

9.3 Middle gray

In photography, painting, and other visual arts, middle gray or middle grey is a tone that is perceptually about halfway between black and white on a lightness scale;[1] in photography, and printing, it is typically defined as 18% reflectance in visible light.[2] This gray reflects exactly 1/5th the number of photons per square unit as compared to a reference white of 90% reflectance.[3] Middle gray is the universal measurement standard in photographic cameras. To calibrate light meters, whether in a camera or hand held, the 18% gray card was conceived. It is assumed that the measurement taken by a meter gives the exposure for a shot so that some of the light reflected by the object measured is equivalent to middle gray.[4] Because human perception adjusts to the overall brightness level (and is logarithmic rather than linear), the perceived middle gray is subjective to the observer. This must be kept in mind when using a camera with a built in light meter (which is not subjective nor logarithmic). Most scenes reflect just 12 % to 13 % of incident light falling upon them. Therefore, the camera light meter assumes a 18% gray level. This can easily be observed when one relies solely, on on the exposure given by a camera with a built in light meter when taking a snow scene - the image will come out dark. Using a 18% gray card as an expose guide will mitigate this error. In the sRGB color space, CIELAB middle gray is equivalent to 46.6% brightness.[5] In 24-bit color, this is rounded to RGB value (119,119,119) or #777777.[6]

9.3.1 History

In the Zone System of Ansel Adams, middle gray is known as “Zone V” in the scale of 11 zones from Zone 0 (black) to Zone X (white).[7] As early as 1903, middle gray was deﬁned as the geometric mean intensity between a white and a black intensity that are in a ratio of 60:1.[8] That is equivalent to 12.9% of the white intensity.

9.3.2 Table of middle grays

Below are various “middle” grays as based on various criterion. In the center of the rendering of the “Absolute whiteness” middle gray, a small black and white checkered image has been included which, if viewed from a distance, should look like a gray with exactly 50% whiteness. On a correctly calibrated sRGB monitor, this should appear to be of equal brightness to rgb(188,188,188) or #BCBCBC.

[1] LCD screens, even when correctly calibrated, often have a brightness that varies considerably depending on the viewing angle. Try stepping back and changing your position until the checkered image in the center of the absolute middle gray (50% relative whiteness) appears to dissolve into the background. If the image does not appear to be of the same brightness, 160 CHAPTER 9. DAY 9

then the “middle grays” rendered in the table are NOT correctly displayed on your screen. (Also take care to make sure your browser window is not zoomed since any magniﬁcation may distort the brightness depending on how your browser adjusts for gamma when blending the pixels, e.g. rendering the zoomed image at sRGB middle gray, or 21% whiteness, instead of 50%.).

9.3.3 References

[1] Stephen Quiller (1999). Painter’s Guide to Color: Includes the New Quiller Color Wheel. Watson-Guptill. ISBN 0-8230- 3913-7.

[2] Blain Brown (2002). Cinematography: Theory and Practice : Imagemaking for Cinematographers, Directors, and Videog- raphers. Focal Press. ISBN 0-240-80500-3.

[3] Woods, Mark. How to Eﬀectively Use the Gray Card. cameraguild.com

[4] Steven Barclay (1999). The Motion Picture Image: From Film to Digital. Focal Press. ISBN 0-240-80390-6.

[5] Geﬀert, Scott (2008). Adopting ISO Standards for Museum Imaging (PDF) (Technical report). imagingetc.com, Inc.

[6] http://www.brucelindbloom.com/index.html?ColorCalculator.html

[7] Jonathan Spaulding (1998). Ansel Adams and the American Landscape: A Biography. University of California Press. ISBN 0-520-21663-6.

[8] Daniel Coit Gilman; Harry Thurston Peck & Frank Moore Colby (1903). The New International Encyclopædia. Dodd, Mead and Company.

9.4 Gray card

18% Gray card (Note: For a precise rendering on a sRGB monitor, see the table in the Middle gray article).

A gray card is a middle gray reference, typically used together with a reﬂective light meter, as a way to produce consistent image exposure and/or color in ﬁlm and photography. 9.4. GRAY CARD 161

Image before (left) and after (right) adjustment with gray card (middle)

A gray card is a flat object of a neutral gray color that derives from a flat reflectance spectrum. A typical example is the Kodak R-27 set, which contains two 8x10” cards and one 4x5” card which have 18% reflectance across the visible spectrum, and a white reverse side which has 90% reflectance. Note that flat spectral reflectance is a stronger condition than simply appearing neutral; this flatness ensures that the card appears neutral under any illuminant (see metamerism).

9.4.1 Application

A major use of gray cards is to provide a standard reference object for exposure determination in photography. A gray card is an (approximate) realization of a Lambertian scatterer; its apparent brightness (and exposure determination) therefore depends only on its orientation relative to the light source. By placing a gray card in the scene to be photographed, oriented toward the direction of the incident light, and taking a reading from it with a reflected light meter, the photographer can be assured of consistent exposures across their photographs. This technique is similar to using an incident meter, as it depends on the illuminance but not the reflectivity of the subject. (Of course taking photographs with side lighting or back lighting implies that the gray card should be oriented toward the camera instead.) In addition to providing a means for measuring exposure, a gray card provides a convenient reference for white balance, or color balance, allowing the camera to compensate for the illuminant color in a scene. Gray cards can be used for in-camera white balance or post-processing white balance. Many digital cameras have a custom white balance feature. A photo of the gray card is taken and used to set white balance for a sequence of photos. For post-processing white balance, a photo of the gray card in the scene is taken, and the image processing software uses the data from the pixels in the gray card area of the photo to set the white balance point for the whole image. Most digital cameras do a reasonable job of controlling color. For the casual user, a gray card is unnecessary. Many serious photographers or hobbyists consider gray cards an essential part of the digital photography process. Gray cards are made of a variety of materials including plastic, paper, and foam. Some photographers hold that any neutral white or gray surface, such as a white piece of paper, a concrete or stone wall, or a white shirt are suitable substitutes for a gray card; however, since bright white papers and clothing washed in typical detergents contain fluorescent whitening agents, they tend to not be very spectrally neutral.[1] Gray cards specially made to be spectrally flat are therefore more suitable to the purpose than surfaces that happen to be available. 162 CHAPTER 9. DAY 9

9.4.2 Limitations

A gray card is only useful for setting or correcting the balance of neutral colors. Other charts, such as various color charts, provide standard reference patterns with calibrated reﬂectance spectrum and color coordinates, for use in adjusting color rendering in a larger range of situations.[2]

9.4.3 References

[1] North Carolina State University (Department of Wood and Paper Science). “FLUORESCENT WHITENING AGENTS (FWAs)". Mini-Encyclopedia of Papermaking Wet-End Chemistry.

[2] Freeman, Michael (2005). The Digital SLR Handbook. Ilex. p. 69. ISBN 1-904705-36-7.

9.4.4 See also

Light meter Chapter 10

Day 10

10.1 List of monochrome and RGB palettes

For a full listing of computer’s color palettes, see List of palettes

This list of monochrome and RGB palettes includes generic repertoires of colors (color palettes) to produce black- and-white and RGB color pictures by a computer’s display hardware, not necessarily the total number of such colors that can be simultaneously displayed in a given text or graphic mode of any machine. RGB is the most common method to produce colors for displays; so these complete RGB color repertoires have every possible combination of R-G-B triplets within any given maximum number of levels per component. For speciﬁc hardware and diﬀerent methods to produce colors other than RGB, see the List of 8-bit computer hardware palettes, the List of 16-bit computer hardware palettes and the List of videogame consoles palettes. For various software arrangements and sorts of colors, including other possible full RGB arrangements within 8-bit color depth displays, see the List of software palettes. Each palette is represented by a series of color patches. When the number of colors is low, a 1-pixel-size version of the palette appears below it, for easily comparing relative palette sizes. Huge palettes are given directly in one-color- per-pixel color patches. For each unique palette, an image color test chart and sample image (truecolor original follows) rendered with that palette (without dithering) are given. The test chart shows the full 256 levels of the red, green, and blue (RGB) primary colors and cyan, magenta, and yellow complementary colors, along with a full 256-level grayscale. Gradients of RGB intermediate colors (orange, lime green, sea green, sky blue, violet, and fuchsia), and a full hue spectrum are also present. Color charts are not gamma corrected.

These elements illustrate the color depth and distribution of the colors of any given palette, and the sample image indicates how the color selection of such palettes could represent real-life images. These images are not necessarily representative of how the image would be displayed on the original graphics hardware, as the hardware may have additional limitations regarding the maximum display resolution, pixel aspect ratio and color placement. For simulated sample images for notable computers, see the List of 8-bit computer hardware palettes and List of 16-bit computer hardware palettes articles.

10.1.1 Monochrome palettes

These palettes only have some shades of gray, from black to white, both considered the most possible darker and lighter “grays”, respectively. The general rule is that those palettes have 2n diﬀerent shades of gray, where n is the number of bits needed to represent a single pixel.

163 164 CHAPTER 10. DAY 10

Monochrome (1-bit)

Monochrome graphics displays typically have a black background with a white or light gray image, though green and amber monochrome monitors were also common. Such a palette requires only one bit per pixel.

Where photo-realism was desired, these early computer systems had a heavy reliance on dithering to make up for the limits of the technology.

In some systems, as Hercules and CGA graphic cards for the IBM PC, a bit value of 1 represents white pixels (light on) and a value of 0 the black ones (light oﬀ); others, like the Atari ST and Apple Macintosh with monochrome monitors, a bit value of 0 means a white pixel (no ink) and a value of 1 means a black pixel (dot of ink), which it approximates to the printing logic.

2-bit Grayscale

In a 2-bit color palette each pixel’s value is represented by 2 bits resulting in a 4-value palette (22 = 4).

2-bit dithering:

It has black, white and two intermediate levels of gray as follows:

A monochrome 2-bit palette is used on:

• NeXT Computer, NeXTcube and NeXTstation monochrome graphic displays.

• Original Game Boy system portable videogame console.

• Macintosh PowerBook 150 monochrome LC displays.

• Commodore Amiga with A2024 monochrome monitor in high-resolution mode.[1]

• The original Amazon Kindle

• The original Wonderswan

4-bit Grayscale

In a 4-bit color palette each pixel’s value is represented by 4 bits resulting in a 16-value palette (24 = 16):

4-bit grayscale dithering does a fairly good job of reducing visible banding of the level changes: 10.1. LIST OF MONOCHROME AND RGB PALETTES 165

A monochrome 4-bit palette is used on:

• MOS Technology VDC (on the Commodore 128 with monochrome monitor) • Amstrad CPC series with a GT64/GT65 Green Monitor (16 unique green shades) • Amstrad CPC Plus series with the MM12 Monochrome monitor (16 shades of grey) • Some Apple PowerBooks equipped with monochrome displays like the PowerBook 5300

8-bit Grayscale

In an 8-bit color palette each pixel’s value is represented by 8 bits resulting in a 256-value palette (28 = 256). This is usually the maximum number of grays in ordinary monochrome systems; each image pixel occupies a single memory byte.

Most scanners can capture images in 8-bit grayscale, and image ﬁle formats like TIFF and JPEG natively support this monochrome palette size. Alpha channels employed for video overlay also use (conceptually) this palette. The gray level indicates the opacity of the blended image pixel over the background image pixel.

10.1.2 Dichrome palettes

16-bit RG palette

Main article: RG color space

16-bit RB palette

16-bit GB palette

10.1.3 Regular RGB palettes

Here are grouped those full RGB hardware palettes that have the same number of binary levels (i.e., the same number of bits) for every red, green and blue components using the full RGB color model. Thus, the total number of colors are always the number of possible levels by component, n, raised to a power of 3: n×n×n = n3. 166 CHAPTER 10. DAY 10

3-bit RGB

3-bit RGB dithering:

Systems with a 3-bit RGB palette use 1 bit for each of the red, green and blue color components. That is, each component is either “on” or “oﬀ” with no intermediate states. This results in an 8-color palette ((21)3 = 23 = 8) that have black, white, the three RGB primary colors red, blue and green and their correspondent complementary colors cyan, magenta and yellow as follows:

The color indices vary between implementations; therefore, index numbers are not given. The 3-bit RGB palette is used by:

• The ECMA-48 standard for text terminals (sometimes known as the “ANSI standard”, although ANSI X3.64 does not deﬁne colors)

• Teletext Level 1/1.5 Teletext.

• Videotex

• TRS-80 Color Computer (in graphics mode, only 4 colors can be displayed simultaneously from ﬁxed 4-colors palettes)

• Oric

• BBC Micro

• The original NEC PC8801 up to the MkII

• The original NEC PC9801 with original 8086 CPU before the VM/VX models

• All Sharp X1 models before the X1 Turbo Z

• The Sharp MZ 700

• Fujitsu FM-7, FM New 7, FM 77 before the FM77AV

• Sinclair QL

• The Macintosh SE with a color printer or external monitor

• The SECAM version of the Atari 2600

• The Color Maximite, a PIC32 based microcomputer

6-bit RGB

Systems with a 6-bit RGB palette use 2 bits for each of the red, green, and blue color components. This results in a (22)3 = 43 = 64-color palette as follows: 10.1. LIST OF MONOCHROME AND RGB PALETTES 167

6-bit RGB systems include the following:

• Enhanced Graphics Adapter (EGA) for IBM PC/AT (only 16 colors can be displayed simultaneously) • Sega Master System videogame console • GIME for TRS-80 Color Computer 3 (only 16 colors can be displayed simultaneously) • Pebble Time smartwatch which has a 6-bit (64 color) e-paper display

9-bit RGB

Systems with a 9-bit RGB palette use 3 bits for each of the red, green, and blue color components. This results in a (23)3 = 83 = 512-color palette as follows:

9-bit RGB systems include the following:

• Atari ST (Normally 4 to 16 at once without tricks) • MSX2 computers (up to 256 at once) • Sega Genesis videogame console (64 at once) • Sega Nomad • TurboGrafx-16 (NEC PC-Engine) • The NEC PC8801 Mk II SR and later models (8 of them at once) • The Mindset computer

12-bit RGB

Systems with a 12-bit RGB palette use 4 bits for each of the red, green, and blue color components. This results in a (24)3 = 163 = 4096-color palette as follows:

12-bit RGB systems include the following: 168 CHAPTER 10. DAY 10

• Amiga OCS/ECS (32, 64, or 4,096 colors)

• Apple IIgs Video Graphics Chip (3,200 colors)

• Atari STe (16 colors)

• Acorn Archimedes

• Sega Game Gear (32 colors)

• Hi-Text Level 2.5+ Teletext

• Neo Geo Pocket Color (147 colors)

• Atari Lynx (16 colors)

• NEC PC-9801 VM/VX models typically equipped with a NEC V30 or better, but before the PC9821 Series.

• The Sharp X1 Turbo Z Series

• Fujitsu FM-77AV

• The Amstrad CPC 664Plus, 6128Plus and GX4000 (32 colors)

• NeXTstation Color and NeXTstation Turbo Color

• WonderSwan Color

15-bit RGB

Systems with a 15-bit RGB palette use 5 bits for each of the red, green, and blue color components. This results in a (25)3 = 323 = 32,768-color palette (commonly known as Highcolor) as follows:

15-bit systems include:

• Super Nintendo Entertainment System (256 colors)

• Truevision TARGA and AT-Vista graphic cards for IBM PC-AT and compatibles, and NU-Vista for Apple Macintosh

• Later models of Super VGA (SVGA) IBM PC compatible graphic cards

• Nintendo Game Boy Color/Advance/SP/Micro pocket videoconsoles

• Nintendo DS (2D output)

• Neo Geo AES/Neo Geo CD videogame consoles (4096 colors)

• The Sega 32X Addon for the Mega Drive/Genesis 10.1. LIST OF MONOCHROME AND RGB PALETTES 169

18-bit RGB

Systems with an 18-bit RGB palette use 6 bits for each of the red, green, and blue color components. This results in a (26)3 = 643 = 262,144-color palette as follows:

18-bit RGB systems include the following:

• Video Graphics Array (VGA) for IBM PS/2 and IBM PC compatibles (256 simultaneous colors from a palette of 262,144)

• Atari Falcon (256 colors)

• Nintendo DS (3D output and 2D blended output)

• Used internally by many LCD monitors

24-bit RGB

Often known as truecolor and millions of colors, 24-bit color is the highest color depth normally used, and is available on most modern display systems and software. Its color palette contains (28)3 = 2563 = 16,777,216 colors. This is 170 CHAPTER 10. DAY 10

All 16,777,216 colors (downscaled, click image for full resolution). approximately the number of individual colors the human eye can distinguish within the limited gamut of a typical display. The complete palette (shown above) needs a squared image of 4,096 pixels wide (50.33 MB uncompressed), and there is not enough room in this page to show it at full. This can be imagined as 256 stacked squares like the following, every one of them having the same given value for the red component, from 0 to 255. The color transitions in these patches must be seen as continuous. If you see color stepping (banding) inside, then probably your display is using a Highcolor (15- or 16- bits RGB, 32,768 or 65,536 colors) mode or lesser.

This is also the number of colors used in true color image ﬁles, like Truevision TGA, TIFF, JPEG (the last internally encoded as YCbCr) and Windows Bitmap, captured with scanners and digital cameras, as well as those created with 3D computer graphics software. 24-bit RGB systems include:

• Amiga Advanced Graphics Architecture (256 or 262144 colors) 10.1. LIST OF MONOCHROME AND RGB PALETTES 171

• Nintendo 3DS

• PlayStation Vita

• Later models of Super VGA (SVGA) IBM PC compatible graphic cards

• Truevision AT-Vista graphic cards for IBM PC-AT and compatibles, and NU-Vista for Apple Macintosh.

• The Philips CD-i

30-bit RGB

Some newer graphics cards support 30-bit RGB and higher. Its color palette contains (210)3 = 10243 = 1,073,741,824 colors. However, there are few operating systems or applications that support this mode yet. For some people, it may be hard to distinguish between higher color palettes than 24-bit color oﬀers. However, the range of luminance, or gray scale, oﬀered in a 30-bit color system would have 1,024 levels of luminance rather than the 256 of the common standard 24-bit, to which the human eye is more sensitive than to hue.

10.1.4 Non-regular RGB palettes

These also are full RGB palette repertories, but either they do not have the same number of levels for every red, green and blue components, or they are bit levels based. Nevertheless, all of them are used in very popular personal computers. For further details on color palettes for these systems, see the article List of 8-bit computer hardware palettes.

4-bit RGBI

The 4-bit RGBI palette is similar to the 3-bit RGB palette but adds one bit for intensity. This results in each of the colors of the 3-bit palette to have a dark and bright variant giving a total of 23×2 = 16 colors. This 4-bits RGBI schema is used in several platforms with variations, so the table given below is a simple reference for the palette richness, and not an actual implemented palette. For this reason, no numbers are assigned to each color, and color order is arbitrary.

Note that “dark white” is a lighter gray than “bright black”. The 4-bits RGBI palettes are used by:

• Color Graphics Adapter, with brown instead of dark yellow). On CGA, setting a color “bright” added ⅓ of the maximum to all three channels’ brightness, so the “bright” colors were whiter shades of their 3-bit counterparts. Each of the other bits increased a channel by ⅔, except that dark yellow had only ⅓ green and was therefore brown instead of ochre.

• The CGA palette was the default for EGA, VGA and Microsoft Windows 3.x (on the IBM PC and compatibles), although other palettes were available.

• MOS Technology VDC (on the Commodore 128)

• ZX Spectrum (with two black, black with bright is the same as black without bright) 172 CHAPTER 10. DAY 10

• TI 99/4A / MSX (These use the TMS9918 video chip. The colors do not conform to the image above, but has instead: transparency, black, medium green, light green, dark blue, dark purple, brown, cyan, dark red, orange, dark yellow, light yellow, dark green, medium purple, gray, and white.)

• Sharp MZ 800

3-level RGB

The 3-level ('not' bits) RGB uses three level for every red, green and blue color components, resulting in a 33 = 27 colors palette as follows:

This palette is used by:

• The Amstrad CPC 464 series of personal computers excluding the Plus models

• The Toshiba Pasopia 7

3-3-2 bit RGB

The 3-3-2 bit RGB use 3 bits for each of the red and green color components, and 2 bits for the blue component, due to the lesser sensitivity of the common human eye to this primary color. This results in an 8×8×4 = 256-color palette as follows:

This palette is used by

• The MSX2 series of personal computers.

• Palette 4 of the IBM PGC (palette 2 gives 2-3-3 bit RGB and palette 3 gives 3-2-3 bit RGB).

• VGA built-in output of the Digilent Inc. NEXYS 2, NEXYS 3 and BASYS2 FPGA boards.

• The Uzebox gaming console

• SGI Indy 8-bit XL graphics

• The Tiki 100 personal computer (only 16 colors can be displayed simultaneously) 10.1. LIST OF MONOCHROME AND RGB PALETTES 173

16-bit RGB

Most modern systems support 16-bit color. It is sometimes referred to as Highcolor (along with the 15-bit RGB), medium color or thousands of colors. It utilizes a color palette of 32×64×32 = 65,536 colors. Usually, there are 5 bits allocated for the red and blue color components (32 levels each) and 6 bits for the green component (64 levels), due to the greater sensitivity of the common human eye to this color. This doubles the 15-bit RGB palette. The 16-bit RGB palette using 6 bits for the green component:

The Atari Falcon and the Extended Graphics Array (XGA) for IBM PS/2 use the 16-bit RGB palette. It must be noticed that not all systems using 16-bit color depth employ the 16-bit, 32-64-32 level RGB palette. Platforms like Sharp X68000 or the Neo Geo videogame console employs the 15-bit RGB palette (5 bits are used for red, green, and blue), but the last bit specifies a less significant intensity or luminance. The 16-bit mode of the Truevision TARGA/AT-Vista/NU-Vista graphic cards and its associated TGA file format also uses 15-bit RGB, but it devotes its remaining bit as a simple alpha channel for video overlay. The Atari Falcon can also be switched into a matching mode by setting of an “overlay” bit in the graphics processor mode register when in 16-bit mode, meaning it can actually display in either 15- or 16-bit color depth depending on application.

10.1.5 See also

• Palette (computing)

• Indexed color

• Color Lookup Table

• Computer display

• List of home computers by video hardware

• Bitmap

• Grayscale

10.1.6 Notes

[1] “Commodore: A2024”. 174 CHAPTER 10. DAY 10

10.1.7 External links and sources

• HTML Color Codes Dynamic color palette with HTML color codes information

10.2 Impossible color

“Reddish green” redirects here. Reddish Green is also a place in Reddish, Stockport, in Greater Manchester in England. Impossible colors or forbidden colors are supposed colors that cannot be perceived in normal seeing of light that

The human eye’s red-to-green and blue-to-yellow values of each one-wavelength visible color is a combination of various intensities of the various frequencies of visible light, but are reported to be seen in special circumstances.

10.2.1 Types

These impossible colors are of two types:

1. Colors that would be seen if the output strengths of the human eye retina's three types of cone cell (red, green, blue) could be set to values which cannot be produced by exposing the eye in normal seeing conditions to any possible combination of strengths of the frequencies of visible light.

2. Colors that cannot be seen directly from any combination of retina signal output from one place in one eye, but can be generated in the brain’s visual cortex by mixing color signals from the two eyes, or from more than one part of the same eye. Examples of these colors are bluish-yellow and reddish-green.[1] Those colors that appear to be similar to, for example, both red and green, or to both yellow and blue. (This does not mean the result of mixing paints of those two colors in painting, or the result of mixing lights of those two colors on a screen.) 10.2. IMPOSSIBLE COLOR 175

1.0 S ML 0.8

0.6

0.4

0.2

0 400 450 500 550 600 650 700

Normalized spectral sensitivity curves of the three kinds of cone cells, which deﬁne the space of human color sensation

10.2.2 Opponent process

Main article: Opponent process

The color opponent process is a color theory that states that the human visual system interprets information about color by processing signals from cone and rod cells in an antagonistic manner. The three types of cone cells have some overlap in the wavelengths of light to which they respond, so it is more eﬃcient for the visual system to record diﬀerences between the responses of cones, rather than each type of cone’s individual response. The opponent color theory suggests that there are three opponent channels:

• Red versus green.

• Blue versus yellow

• Black versus white (this is achromatic and detects light-dark variation, or luminance).

Responses to one color of an opponent channel are antagonistic to those to the other color, and signals output from a place on the retina can contain one or the other but not both, for each opponent pair.

10.2.3 Real colors

Real colors are colors that can be produced by a physical light source. Any additive mixture of two real colors is also a real color. When colors are displayed in the CIE 1931 XYZ color space, additive mixture results in a color along the line between the colors being mixed. By mixing any three colors, one can therefore create any color contained in the triangle they describe—this is called the gamut formed by those three colors, which are called primary colors. Any colors outside of this triangle cannot be obtained by mixing the chosen primaries. 176 CHAPTER 10. DAY 10

When deﬁning primaries, the goal is often to leave as many real colors in gamut as possible. Since the region of real colors is not a triangle (see illustration), it is not possible to pick three real colors that span the whole region. The gamut can be increased by selecting more than three real primary colors, but since the region of real colors is not a polygon, there always will be some colors at the edge left out. Therefore, one selects colors outside of the region of real colors as primary colors; in other words, imaginary primary colors. Mathematically, the gamut created in this way contains so-called “imaginary colors”. In computer and television screen color displays, the corners of the gamut triangle are deﬁned by commercially available phosphors chosen to be as near as possible to pure red and pure green and pure blue, and thus are within the area of real colors; note that these color space diagrams inevitably display, instead of real colors outside your computer screen’s gamut triangle, the nearest color which is inside the gamut triangle. See page Gamut for more information about the color range available on display devices.

10.2.4 Imaginary colors

One type of imaginary color (also referred to as non-physical or unrealizable color) is a point in a color space that corresponds to combinations of cone cell responses in one eye, that cannot be produced by the eye in normal circumstances seeing any possible light spectrum.[2] Thus, no object can have an imaginary color. But such imaginary colors are useful as mathematical abstractions for deﬁning color spaces. The spectral sensitivity curve of medium-wavelength (“M”) cone cells overlaps those of short-wavelength (“S”) and long-wavelength (“L”) cone cells. Light of any wavelength that interacts with M cones also interacts with S or L cones, or both, to some extent. Therefore, no wavelength (except perhaps a bit of the far red), and no non-negative spectral power distribution, excites only one sort of cone. If, for example, M cones could be excited alone, this would make the brain see an imaginary color greener than any physically possible green; producing it by seeing light would need some of the red and blue parts of visible light to have negative power, which is impossible. Such a “hyper-green” color would be in the CIE 1931 color space chromaticity diagram (left image to the right) in the blank area above the colored area and between the y-axis and the line x+y=1.

10.2.5 Chimerical colors

A chimerical color is an imaginary color that can be seen temporarily by looking steadily at a strong color for a while until some of the cone cells become fatigued, temporarily changing their color sensitivities, and then looking at a markedly diﬀerent color. They are explained by the opponent process color theory.[3] For example, staring at a saturated primary-color ﬁeld then looking at a white object results in an opposing shift in hue, causing an afterimage of the complementary colors. Exploration of the color space outside the range of “real colors” by this means is major corroborating evidence for the opponent process theory of color vision. Chimerical colors can be seen while seeing with one eye or with both eyes, and are not observed to reproduce simultaneously qualities of opposing colors (e.g. “yellowish blue”).[3] Chimerical colors include:

• Stygian colors: these are simultaneously dark and impossibly saturated. For example, to see “stygian blue": staring at bright yellow causes a dark blue afterimage, then on looking at black, the blue is seen as blue against the black, but due to lack of the usual brightness contrast it seems to be as dark as the black. The eye retina contains some neurons that ﬁre only in the dark.

• Self-luminous colors: these mimic the eﬀect of a glowing material, even when viewed on a medium such as paper, which can only reﬂect and not emit its own light. For example, to see “self-luminous red": staring at green causes a red afterimage, then on looking at white, the red is seen against the white and may seem to be brighter than the white.

• Hyperbolic colors: these are impossibly highly saturated. For example, to see “hyperbolic orange": staring at bright cyan causes an orange afterimage, then on looking at orange, the resulting orange afterimage seen against the orange background may cause an orange color purer than the purest orange color that can be made by any normally-seen light. Or, staring at something pure magenta in bright sunlight for two minutes or more, and then looking at green leaves, may result in brieﬂy seeing an unnaturally pure green afterimage. 10.2. IMPOSSIBLE COLOR 177

By staring at a “fatigue template” for 20-60 seconds, then switching to a neutral target, it is possible to view “impossible” colors.

Some people may be able to see the color “yellow–blue” in this image by letting their eyes cross so that both + symbols are on top of each other

10.2.6 Claimed evidence for ability to see impossible colors not in the color space

Under normal circumstances, there is no hue that one could describe as a mixture of opponent hues; that is, as a hue looking “redgreen” or “yellowblue”. 178 CHAPTER 10. DAY 10

In 1983, Hewitt D. Crane and Thomas P. Piantanida performed tests using an eye-tracker device that had a field of a vertical red stripe adjacent to a vertical green stripe, or several narrow alternating red and green stripes (or in some cases, yellow and blue instead). The device could track involuntary movements of one eye (there was a patch over the other eye) and adjust mirrors so the image would follow the eye and the boundaries of the stripes were always on the same places on the eye’s retina; the field outside the stripes was blanked with occluders. Under such conditions, the edges between the stripes seemed to disappear (perhaps due to edge-detecting neurons becoming fatigued) and the colors flowed into each other in the brain’s visual cortex, overriding the opponency mechanisms and producing not the color expected from mixing paints or from mixing lights on a screen, but new colors entirely, which are not in the CIE 1931 color space, either in its real part or in its imaginary parts. For red-and-green, some saw an even field of the new color; some saw a regular pattern of just-visible green dots and red dots; some saw islands of one color on a background of the other color. Some of the volunteers for the experiment reported that afterwards, they could still imagine the new colors for a period of time.[1]

Some observers indicated that although they were aware that what they were viewing was a color (that is, the ﬁeld was not achromatic), they were unable to name or describe the color. One of these observers was an artist with a large color vocabulary. Other observers of the novel hues described the ﬁrst stimulus as a reddish-green.[4]

In 2001 Vincent A. Billock and Gerald A. Gleason and Brian H. Tsou set up an experiment to test a theory that the 1983 experiment did not control for variations in the perceived luminance of the colors from subject to subject: two colors are equiluminant for an observer when rapidly alternating between the colors produces the least impression of ﬂickering. The 2001 experiment was similar but controlled for luminance.[5] They had these observations:

Some subjects (4 out of 7) described transparency phenomena—as though the opponent colors originated in two depth planes and could be seen, one through the other. ... We found that when colors were equiluminant, subjects saw reddish greens, bluish yellows, or a multistable spatial color exchange (an entirely novel perceptual phenomena [sic]); when the colors were nonequiluminant, subjects saw spurious pattern formation.

This led them to propose a “soft-wired model of cortical color opponency”, in which populations of neurons compete to ﬁre and in which the “losing” neurons go completely silent. In this model, eliminating competition by, for instance, inhibiting connections between neural populations can allow mutually exclusive neurons to ﬁre together.[5] Hsieh and Tse in 2006 disputed the existence of colors forbidden by opponency theory and claimed they are, in reality, intermediate colors.[6] See also binocular rivalry.

In synesthetes

Some individuals with X → color synesthesia claim to be able to perceive impossible colors when, for example, two nearby letters have opposing colors. So, someone who has grapheme → color synesthesia, and who considers a to be red and n to be green might be able to perceive red-green if these two letters occur consecutively, like in the word an.

10.2.7 See also

• Bastard color: in theatre lighting, typically in a color gel, a color blended with small amounts of complementary colors.

• Color

• Color mixing

• Color vision

• False-color image, an image that depicts an object in colors that diﬀer from those that a visible-colors-only photograph would show.

• Middle gray, a shade of gray used to adjust photographs to match perceptual brightness as opposed to absolute brightness as measured by a digital camera. 10.2. IMPOSSIBLE COLOR 179

• Spectral color

• Tetrachromacy, having four primary colors • Non-visible electromagnetic waves, such as radio waves, microwaves, X-rays, etc.

• List of fictional colors, mostly as seen by fictional aliens whose eyes work differently from human eyes.

10.2.8 References

[1] Crane, Hewitt D.; Piantanida, Thomas P. (1983). “On Seeing Reddish Green and Yellowish Blue”. Science. 221 (4615): 1078–80. doi:10.1126/science.221.4615.1078. JSTOR 1691544. PMID 17736657.

[2] MacEvoy, Bruce (2005). “Light and the eye”. Handprint. Retrieved May 5, 2007.

[3] Churchland, Paul (2005). “Chimerical Colors: Some Phenomenological Predictions from Cognitive Neuroscience”. Philo- sophical Psychology. 18 (5): 527–560. doi:10.1080/09515080500264115.

[4] Suarez J; Suarez, Juan (2009). “Reddish Green: A Challenge for Modal Claims About Phenomenal Structure”. Philosophy and Phenomenological Research. 78 (2): 346–391. doi:10.1111/j.1933-1592.2009.00247.x.

[5] Billock, Vincent A.; Gerald A. Gleason; Brian H. Tsou (2001). “Perception of forbidden colors in retinally stabilized equiluminant images: an indication of softwired cortical color opponency?" (PDF). Journal of the Optical Society of America A. Optical Society of America. 18 (10): 2398–2403. doi:10.1364/JOSAA.18.002398. Retrieved 2010-08-21.

[6] Hsieh, P.-J.; Tse, P. U. (2006). “Illusory color mixing upon perceptual fading and ﬁlling-in does not result in “forbidden colors"". Vision Research. 46 (14): 2251–8. doi:10.1016/j.visres.2005.11.030. PMID 16469353.

• Imaginary Colors, Real Results, Dan Margulis, July, 2005

10.2.9 Further reading

• Billock, Vincent A.; Tsou, Brian H. (2010). “Seeing Forbidden Colors”. Scientiﬁc American. 302 (2): 72–7. doi:10.1038/scientiﬁcamerican0210-72. PMID 20128226.

• Takahashi, Shigeko; Ejima, Yoshimichi (1984). “Spatial properties of red-green and yellow-blue perceptual opponent-color response”. Vision Research. 24 (9): 987–94. doi:10.1016/0042-6989(84)90075-0. PMID 6506487. • Hibino, H (1992). “Red-green and yellow-blue opponent-color responses as a function of retinal eccentricity”. Vision Research. 32 (10): 1955–64. doi:10.1016/0042-6989(92)90055-n. PMID 1287992.

10.2.10 External links

• Bradbury, Aaron (Mar 1, 2014). “Hyperbolic Orange and the River to Hell”. It is possible however to see colours that aren’t in reality. Impossible colours... Chapter 11

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TEXT AND IMAGE SOURCES, CONTRIBUTORS, AND LICENSES

MeanMotherJr, BattyBot, Guanaco55, Justincheng12345-bot, Brodyisnumber1, Mtorgoman, Pratyya Ghosh, Cyberbot II, The Illusive Man, Harm01, Horsesandponies45152, Krystaleen, JYBot, IjonTichyIjonTichy, Cmw255, Harsh 2580, Dexbot, Webclient101, Ruthand- kyle, Jatinag22, Oliviamcnamara, Westykraft, Omegahollow1234, Lugia2453, Ak5791, Frosty, SFK2, EatIcecream2, Kiieu57, Jochen Burghardt, Natasha pokeware, Lucyeuington, Silver Cat Tails, Wywin, NightShadow23, Xxnerdzillaxx, BillyMays232, Mr.woisard, Cadil- lac000, Doomedfella989, Reatlas, Fatjoe23343, Isoccer00, Epicgenius, Msartakov, Wajidkanju, Howicus, Artchick27, Eyesnore, Dl- dude2k14, PhantomTech, Everymorning, Mookers13, Johnscotaus, Natimosquera, CokeHanx, CensoredScribe, Editingeditors, Intro123, Sibekoe, Ugog Nizdast, Ginsuloft, Robinesque, Jagannath mango, Quenhitran, Philcourt94, Axeman225, EverythingGeography, My- nameissachin, Aubreybardo, Lizia7, Krotera, TheOrangePuff, Evan Guthrie, MilmolbelGaming, Jmoctopus, Sontic, 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Discospinster, Vsmith, Kwamikagami, Lysdexia, Echuck215, W7KyzmJt, Falcorian, Jacobolus, John- rpenner, Ysangkok, GünniX, Glenn L, Chobot, Banaticus, Tommylommykins, Wavelength, RussBot, DMahalko, Stephenb, PanchoS, StuRat, Theda, Pb30, SmackBot, Reedy, Argyriou, VMS Mosaic, Dreadstar, Slakr, Childzy, Dicklyon, Az1568, Courcelles, Patrick- wooldridge, Ale jrb, CBM, WeggeBot, Sam Staton, Zalgo, Thijs!bot, Epbr123, Keraunos, Marek69, Dalahäst, Missvain, RFerreira, Fotomatt, Obiwankenobi, Ishikawa Minoru, Captin Shmit, Bus stop, CommonsDelinker, J.delanoy, SharkD, Darkspots, Arms & Hearts, KylieTastic, Tkgd2007, Sporti, Philip Trueman, ElinorD, LeaveSleaves, VanBuren, The Random Editor, StAnselm, Phe-bot, Vanished user 82345ijgeke4tg, Pi is 3.14159, Acet0ne, Spark Moon, Ogre lawless, IdreamofJeanie, Svick, Randy Kryn, Danart474, Sagredo, Tanvir Ahmmed, ClueBot, Chaveso, Rockfang, Excirial, Erebus Morgaine, Gtstricky, Razorflame, Dekisugi, Taranet, Skarebo, Trondg, Addbot, ,חובבשירה 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Huritisho, Gab- byhi216, Marianna251, Clawraich (Dalek), Bender the Bot, Iambic Pentameter, Trash-Mobile, Lars0164 and Anonymous: 238 • Spectral color Source: https://en.wikipedia.org/wiki/Spectral_color?oldid=751831540 Contributors: AxelBoldt, AJim, RcktScientistX, Decoy, Wrs1864, Bobrayner, Jacobolus, BD2412, NekoDaemon, Adoniscik, Benandorsqueaks, Segv11, SmackBot, Incnis Mrsi, Nbarth, VMS Mosaic, Lambiam, Anlace, Bjankuloski06en~enwiki, Tothedark, Ben Moore, Dicklyon, Guyburns, Monni95, Richard75, Nils- son~enwiki, SonicBlue, Keraunos, Magioladitis, Swpb, Spayneuter, Tadpole9, Belovedfreak, Lygophile, Spiral5800, T Arrow, ChrisHodge- sUK, Addbot, Da5nsy, Luckas-bot, Aboalbiss, AnomieBOT, Limetang, Erik9bot, Cnwilliams, WikitanvirBot, ChuispastonBot, Oinkers192, ClueBot NG, Wbm1058, Gluonman, Crocodilesareforwimps, Zyxwv99, FoCuSandLeArN, PotatoNinja, NoToleranceForIntolerance and Anonymous: 34 • Color space Source: https://en.wikipedia.org/wiki/Color_space?oldid=757562790 Contributors: Damian Yerrick, Zundark, Heron, Branko, Alan Peakall, Dominus, Wapcaplet, MichaelJanich, CesarB, Cyp, LittleDan, Jay, Gutza, Hyacinth, Grendelkhan, Bevo, Denelson83, Robbot, Noldoaran, Fredrik, Mfc, DocWatson42, Seabhcan, Brona, Asc99c, Guanaco, Avsa, Darrien, Sven271, Sam Hocevar, Hellisp, Uaxuctum~enwiki, Ta bu shi da yu, Poccil, CALR, Richie, Josef Meixner~enwiki, Rich Farmbrough, Guanabot, Smyth, Notinasnaid, SocratesJedi, Alue, Dkroll2, Bobo192, Dmurphy, Arthena, Kasper Hviid, PAR, Suruena, Forderud, Aadnk, Mindmatrix, Jacobolus, Cy21, Eyreland, Umofomia, Sparkit, BD2412, Rjwilmsi, NekoDaemon, Chobot, Adoniscik, Roboto de Ajvol, YurikBot, ENeville, Jonathan Webley, Retired username, Tetracube, BorgQueen, LeonardoRob0t, Benandorsqueaks, Cmglee, Sardanaphalus, SmackBot, FishSpeaker, Moeron, Gilliam, Brianski, Chris the speller, Bluebot, VMS Mosaic, Seattlenow, Aditsu, Rythie, IronGargoyle, Beetstra, Waggers, Rhebus, Dr.K., Aursani, Cxw, ISteve, Chrumps, Aubrey Jaffer, Tletnes, Cpesacreta, Martin Hogbin, AgentPeppermint, Es- carbot, Lovibond, Sluzzelin, The Transhumanist, Sterrys, DariusMonsef, Colordoc, 28421u2232nfenfcenc, Ashishbhatnagar72, R'n'B, Pharaoh of the Wizards, Normankoren, SharkD, Robartsd, Mufka, KylieTastic, Ale2006, Funandtrvl, Rebornsoldier, Odo1982, Ratuliut, Neparis, SieBot, Dwandelt, Marluxia.Kyoshu, Blacklemon67, ClueBot, Ficbot, Lambtron, Life of Riley, Misst r, Skarebo, Druj Nasu, Addbot, Kbseah, Lightbot, Aboalbiss, AnomieBOT, Jim1138, Sellyme, Twirligig, Dave3457, Jolbas, North8000, Chrisc666, Diannaa, Jhenderson777, Woodlot, Look2See1, Stephanej, Dcirovic, ZéroBot, Ὁ οἶστρος, Joeyvandernaald, ChuispastonBot, EdoBot, ClueBot NG, AlbertBickford, This lousy T-shirt, BarrelProof, BG19bot, AUllrich, Conifer, SarahPalmerson, Makecat-bot, UNOwenNYC, Or- angeNapkin, DavRosen, Kind Tennis Fan, Brockwattage, Tony0517, Rhyiana, Me-in-nk, Colorchaser, Fmadd, Bender the Bot, Jennifer Paul and Anonymous: 124 • ColorChecker Source: https://en.wikipedia.org/wiki/ColorChecker?oldid=751848863 Contributors: Bearcat, Jacobolus, Cmglee, Ma- gioladitis, Glrx, Nono64, Oshwah, No such user, The Founders Intent, Sun Ladder, Humbleweed, Sbmeirow, InternetArchiveBot and Anonymous: 7 • Primary color Source: https://en.wikipedia.org/wiki/Primary_color?oldid=764017693 Contributors: Damian Yerrick, AxelBoldt, Lee Daniel Crocker, Bryan Derksen, Waveguy, Heron, Ram-Man, Wapcaplet, Ellywa, Ahoerstemeier, ToastyKen, Vzbs34, Arteitle, BenRG, Northgrove, Chuunen Baka, Robbot, DHN, Hadal, Bryno, Bkonrad, Niteowlneils, Chinasaur, Erdal Ronahi, Yekrats, Jackol, LiDaob- ing, Beland, MFNickster, Maneesh, Melonhead, Tsemii, Quota, Discospinster, Rhobite, Supercoop, YUL89YYZ, Triskaideka, Chewie, Dkroll2, Hayabusa future, Mqduck, Army1987, Myria, La goutte de pluie, Vanished user 19794758563875, Haham hanuka, Alansohn, Trjumpet, Carioca, Bsadowski1, Kazvorpal, Nuno Tavares, Georgia guy, Jacobolus, Cruccone, Tabletop, Kelisi, Dysepsion, Mandarax, Gemsling, Graham87, Rjwilmsi, MWAK, Margosbot~enwiki, Nihiltres, TheMidnighters, NekoDaemon, Gurch, Addesso, Themissinglint, Glenn L, Chobot, Citizen Premier, Bgwhite, Adoniscik, YurikBot, RussBot, ENeville, DAJF, Mysid, DeadEyeArrow, Cavan, Bmju, FF2010, Thelb4, JDspeeder1, SkerHawx, Sycthos, SmackBot, Moeron, C.Fred, Jab843, Trystan, Gilliam, Chris the speller, Bluebot, DHN-bot~enwiki, Brianhill, Darth Panda, Chlewbot, VMS Mosaic, Nahum Reduta, Dreadstar, Crd721, Tactik, Drc79, Lukeoz, JunC- TionS, Kuru, Stale2000, Butko, Stratadrake, Dicklyon, AEMoreira042281, Avant Guard, Iridescent, Alchav, Shoeofdeath, CapitalR, Freelance Intellectual, Tawkerbot2, Jh12, JForget, Deon, Cxw, WeggeBot, Daveoh, Myasuda, Laura S, Meighan, Mjjj, Christian75, 11.1. TEXT 183

UberScienceNerd, Ohnjaynb, Epbr123, Keraunos, AgentPeppermint, Nick Number, Mjad~enwiki, Mentifisto, AntiVandalBot, Luna Santin, Seaphoto, AxiomShell, MikeLynch, MER-C, Arch dude, PaleAqua, PhilKnight, Acroterion, Magioladitis, Connormah, Bong- warrior, VoABot II, Soulbot, 28421u2232nfenfcenc, Vssun, DerHexer, Nopira, GreggEdwards, MartinBot, Jim.henderson, Neodymion, Glossando, LedgendGamer, J.delanoy, Lucaswilkins, Singularitarian, Javawizard, Onhm, Mrob27, Katalaveno, Thatotherperson, Velps, NewEnglandYankee, DadaNeem, Mike902, Koobmeej, Cmichael, KylieTastic, Cometstyles, EXCEPTION NOT HANDLED, Funandtrvl, VolkovBot, Davidmcb64, TXiKiBoT, Oshwah, The Original Wildbear, Sarenne, Wiikipedian, Ferengi, LeaveSleaves, Fists, Steve3849, Feudonym, Ziphon, Enviroboy, RingWars2007, DrVenture, Chack Jadson, Pi is 3.14159, Keilana, Roosterrulez, Oda Mari, Man It’s So Loud In Here, Shaheenjim, JSpung, KoshVorlon, Paulhiphop, Manway, Cult of the Sacred Or nge, Sunrise, OKBot, Anchor Link Bot, 48states, ClueBot, TransporterMan, The Thing That Should Not Be, Kathartic, Maggiewoo, Doyleb23, ChandlerMapBot, Monster boy1, Resoru, VRBones, Jotterbot, Ertemplin, Porridgebowl, Crowsnest, DumZiBoT, I*Rok*U*Dont, InternetMeme, Matta96, Ost316, Avoided, WikHead, Joyonicity, MystBot, Tayste, Addbot, Some jerk on the Internet, DOI bot, Wsvlqc, Aitrea, West.andrew.g, Emdrgreg, Tide rolls, Ben Ben, आशीष भटनागर, Luckas-bot, TheSuave, Yobot, Fraggle81, AnomieBOT, DemocraticLuntz, 1exec1, Götz, Jim1138, Materialscientist, Citation bot, Raven1977, Andrewmc123, Xqbot, HN45, Avicek, J04n, RibotBOT, Kickyandfun, Gerge125, CES1596, VS6507, Mfwitten, Citation bot 1, Javert, Pinethicket, I dream of horses, Captain Virtue, Jmmmmmm, White Shadows, Ticklewick- leukulele, Jonkerz, SDLarsen, Weedwhacker128, Jhenderson777, Fastilysock, Minimac, RjwilmsiBot, P Aculeius, EmausBot, Orphan Wiki, Dcirovic, Fæ, Sicklounge, Lacain247, Ocean Shores, TyA, L Kensington, VictorianMutant, TYelliot, Helpsome, ClueBot NG, Chocolate beans69, Snotbot, Widr, Helpful Pixie Bot, Strike Eagle, BG19bot, GreyAlien502, Whatthehell123, Max Ijzersteen, Fer408, Rockgirl745, BabyD1994, Wannabemodel, Jossian, Krystaleen, Mogism, Cerabot~enwiki, AkashBedi12, GranChi, Hpugh123, Me, My- self, and I are Here, Jeremy.usman33, ZIADMAJ, DavidLeighEllis, CensoredScribe, Kharkiv07, Atotalstranger, Noyster, Monkbot, KH-1, Grami210, MrGesham, Lolkittyfish123, Jimbo.sheffield, Shauny6983, CAPTAIN RAJU, CitrusEllipsis, Bigbluesky88, The liar2, DoraemonGamer, Carilchasens, Bender the Bot, L3X1, Evildrprokchop, Jefjulia40 and Anonymous: 483 • Tertiary color Source: https://en.wikipedia.org/wiki/Tertiary_color?oldid=745383319 Contributors: Donarreiskoffer, Mike Rosoft, YUL89YYZ, Kwamikagami, Smalljim, Alansohn, MarkGallagher, Kazvorpal, Alkarex, Georgia guy, Daniel Case, Jacobolus, Kelisi, Paradoxides~enwiki, Banpei~enwiki, Rjwilmsi, MWAK, NekoDaemon, Glenn L, Bgwhite, Ospalh, Yeryry, Sycthos, SmackBot, Yamaguchi, Bluebot, PawełMM, Can't sleep, clown will eat me, VMS Mosaic, Dicklyon, IvanLanin, Cryptic C62, JForget, Tewapack, Dingbats, Keraunos, Nachmore, SC979, Arch dude, DanPMK, DerHexer, GreggEdwards, The Canadian Roadgeek, Tgeairn, Belovedfreak, Velps, Mike902, Hammersoft, Jeromesyroyal, Kostaki mou, Nice poa, Saturn star, Falcon8765, Meerar20, Flyer22 Reborn, 48states, Mx. Granger, Clue- Bot, Blickmaestro, AlanM1, Soopto, Addbot, Morecambe1, AbruCH, Chamberlain2007, Gail, AnomieBOT, Hairhorn, Xqbot, Bran- don5485, Thehelpfulbot, Pianoplonkers, Anthonyk312, Jhenderson777, P Aculeius, Brainsurge33, Wikipelli, Fæ, ClueBot NG, Frietjes, Helpful Pixie Bot, BG19bot, MB2T1, Silvrous, Mogism, Malcolmmwa, Fench, Muhammad Areez, Loraof, Leo02-2002, Jayjaylyle, ProprioMe OW, GSS-1987, Bender the Bot, Miguel0044 and Anonymous: 106 • Additive color Source: https://en.wikipedia.org/wiki/Additive_color?oldid=751155822 Contributors: Mav, Bryan Derksen, JDG, Michael Hardy, Ellywa, Mxn, Smb1001, Pko, Pengo, Carnildo, Graeme Bartlett, Mormegil, MattTM, Dkroll2, Toh, Jacobolus, Ruud Koot, Ry- oung122, FlaBot, Catsmeat, Gurch, Janke, Bb3cxv, Kkmurray, 21655, Daniel G., SmackBot, Incnis Mrsi, Thorseth, Robbak, Peter Isotalo, Rrburke, VMS Mosaic, Khazar, Loadmaster, Dicklyon, Courcelles, Thijs!bot, Dkrolls, Marokwitz, Tjmayerinsf, MarcLevoy, Nono64, Velps, Thunderbird2, VVVBot, ClueBot, Timberframe, Thingg, Heyzeuss, Ost316, Wyatt915, Addbot, Ronhjones, Legobot, Luckas-bot, 2D, Aboalbiss, Nuttish, Giants27, CindySteve, Maulucioni, Dudered, Erimaxbau, Captain Virtue, Dinamik-bot, Jhender- son777, RjwilmsiBot, Dominus Vobisdu, ZéroBot, AVarchaeologist, Deracination, ClueBot NG, Itzuvit, AvocatoBot, CitationCleaner- Bot, Fizped~enwiki, Spet17, Makecat-bot, Mbreht, TwoTwoHello, GediminasStankevicius, Liz, Crystallizedcarbon, Marianna251, Fly- ingpinkpotato, Bender the Bot, Calnce and Anonymous: 50 • Subtractive color Source: https://en.wikipedia.org/wiki/Subtractive_color?oldid=746760895 Contributors: Michael Hardy, Chris-martin, Delirium, Stib, Mxn, Smack, Dysprosia, Unfree, Craig Butz, Gobeirne, Chinasaur, MisfitToys, CoyneT, Mormegil, Notinasnaid, MattTM, Ntennis, Dkroll2, Shehal, Alansohn, Stack, Daira Hopwood, Jacobolus, Bennetto, Xiong Chiamiov, Glenn L, YurikBot, RobotE, Gaius Cornelius, Fivestrokes, Janke, NickBush24, Wknight94, 21655, OMenda~enwiki, Knotnic, Caballero1967, That Guy, From That Show!, SmackBot, Thorseth, God of War, VMS Mosaic, SashatoBot, Mtodorov 69, Beetstra, Dicklyon, Newone, Reds2010, Tawkerbot2, Fun- nyfarmofdoom, Verdy p, Thijs!bot, Dkrolls, Chickenflicker, AntiVandalBot, Tjmayerinsf, Scepia, JAnDbot, Derek Chong, Bongwar- rior, MarcLevoy, MartinBot, J.delanoy, SharkD, Gtg204y, VolkovBot, Seattle Skier, Bsroiaadn, Shaunv123, ClueBot, Mild Bill Hiccup, Erudecorp, Versus22, Heyzeuss, Jasynnash2, Addbot, LaaknorBot, OlEnglish, Yobot, Nuttish, Citation bot, Xqbot, Kissiepoo102684, Erimaxbau, Serols, Jhenderson777, Stroppolo, AppuruPan, Dcirovic, AVarchaeologist, ClueBot NG, Snotbot, Dreambeaver, Wyken Sea- grave, Liz and Anonymous: 75 • Color mixing Source: https://en.wikipedia.org/wiki/Color_mixing?oldid=759965029 Contributors: Ubiquity, MSGJ, Paul August, Doozer, Shinjin.cr, Brookie, Glenn L, DVdm, Moe Epsilon, Akrabbim, SmackBot, PotatoChipEnjoyer, RomaC, VMS Mosaic, Spinningspark, Flyer22 Reborn, JL-Bot, Excirial, UnCatBot, SF007, Wyatt915, Addbot, Lithoderm, Nuvitauy07, Materialscientist, Tad Lincoln, Lithop- sian, Erimaxbau, Serols, TheBFG, Mean as custard, EmausBot, RA0808, John Cline, ClueBot NG, Jack Greenmaven, Matthiaspaul, Satellizer, Helpful Pixie Bot, David.moreno72, ChrisGualtieri, A.entropy, Bha100710, Epicgenius, Eyesnore, Hisashiyarouin, Sloo7ali, Julietdeltalima, Marloz1800, YlemArt1, Sro23, Sciprod, Zodoggy, Tifmco, Taramcgoff, Ailaeshis and Anonymous: 63 • Color calibration Source: https://en.wikipedia.org/wiki/Color_calibration?oldid=758317552 Contributors: Andrewman327, Hankwang, Drant, Eric Kvaalen, Hohum, Versageek, Gene Nygaard, Jacobolus, Before My Ken, Drbogdan, Rjwilmsi, Ian Dunster, Chyel, Dres- dnhope, Adoniscik, Dhwoow, GraemeL, JLaTondre, SmackBot, KaiUwe, Bluebot, Thumperward, SailorfromNH, Frap, John Hupp, VMS Mosaic, Dicklyon, ChrisCork, VoxLuna, DangerousPanda, Articnomad, NickSpiker, Werd678, Luna Santin, Dylantovey, AGoon, PaleAqua, Z22, Objectivesea, JaffaCakeLover, DrSeehas, [email protected], FisherQueen, Nono64, Wolfganghaak, Lbeaumont, Jepoirrier, Odo1982, Sefidel, Datacolor, Mild Bill Hiccup, SchreiberBike, Birzio, Paul Vernaza, Addbot, Favonian, Sven Boisen, Board- ersparadise, Ceramres, AnomieBOT, Citation bot, LilHelpa, Twentymiles, Hyperhypo, FrescoBot, Calmer Waters, Pestling, TheSuede, WikitanvirBot, ZéroBot, Sbmeirow, Karthikndr, Atcold, Helpful Pixie Bot and Anonymous: 41 • International Color Consortium Source: https://en.wikipedia.org/wiki/International_Color_Consortium?oldid=756347372 Contribu- tors: SJK, Isomorphic, CesarB, Denelson83, AlistairMcMillan, Meat For Mommy, Lintu~enwiki, Notinasnaid, Xezbeth, Chalst, Duk, Hooperbloob, Ruud Koot, Evilmoo, BD2412, Ian Dunster, FlaBot, NekoDaemon, Adoniscik, Whosasking, YurikBot, Wavelength, WulfTheSaxon, Rathfelder, Ratarsed, Thomas Ash, Ultramandk, Frap, Cybercobra, Dicklyon, Chrumps, Thijs!bot, AgentPeppermint, Widefox, JAnDbot, Manorainjan, STBot, Alexbot, Sun Creator, DumZiBoT, Addbot, Ghettoblaster, Lightbot, Luckas-bot, Yobot, Xqbot, ColourTop, Noolander, DissidentAggressor, Philgreen736767 and Anonymous: 9 184 CHAPTER 11. TEXT AND IMAGE SOURCES, CONTRIBUTORS, AND LICENSES

• International Colour Association Source: https://en.wikipedia.org/wiki/International_Colour_Association?oldid=695459596 Contrib- utors: Jhortman, Adoniscik, Harryboyles, OS2Warp, Alaibot, Asarlaí, JL-Bot, Jose Luis Caivano, Staticshakedown, Addbot, Ghetto- blaster, Lightbot, Yobot, JoseCaivano, EricEnfermero, BattyBot, TomoK12 and Anonymous: 3 • Lab color space Source: https://en.wikipedia.org/wiki/Lab_color_space?oldid=763832719 Contributors: Michael Hardy, Sebastian- Helm, Ellywa, Ahoerstemeier, Cherkash, Mulad, Crissov, Dysprosia, Gutza, Omegatron, Samsara, Mina86, Bearcat, Fredrik, 75th Trom- bone, Connelly, Dmmaus, Zeimusu, Tybruce, Kelson, Richie, Notinasnaid, Kjoonlee, Lysdexia, Varuna, PAR, Kdau, Kelly Martin, Mind- matrix, Jacobolus, Spike0xFF, Tabletop, Waldir, TAKASUGI Shinji, Mlewan, NekoDaemon, Adoniscik, Wavelength, IByte, Marcus Cyron, ENeville, Inike, Nick, Anetode, Jaysbro, Burton Radons, SmackBot, Slashme, Mhss, Chris the speller, Konstable, Tsca.bot, VMS Mosaic, Aelffin, Derek farn, SilkTork, Dicklyon, Mfield, LandruBek, Paul Foxworthy, Twas Now, Aoleson, Doceddi, Cxw, Thijs!bot, Glennchan, PhiLiP, Lovibond, CrizCraig, Magioladitis, STBot, UnknownVT, Nono64, Normankoren, Slow Riot, SharkD, Clerks, Dskluz, Motine, Serge925, Nourani~enwiki, Fylwind, STBotD, Remember the dot, Ann McCarthy, Ajfweb, A4bot, Jamelan, Ericeee10, Flyer22 Reborn, Tronic2, VanishedUser sdu9aya9fs787sads, Copyeditor42, Dhoerl, Alexbot, Resoru, Ost316, Addbot, MrOllie, Alpalfour, Yobot, Aboalbiss, AnomieBOT, Efa, Citation bot, Nadia arty, Ll1324, Nagualdesign, FrescoBot, Jiansia, Citation bot 1, Maggyero, Redrose64, Zink Dawg, EmausBot, TuHan-Bot, Bamyers99, Spiritworld, ClueBot NG, Parcly Taxel, Helpful Pixie Bot, Chevreul, NotWith, Leonorek, JYBot, Ruby Murray, John.cumings, Ibrahim Husain Meraj, AndyThe, Brainiacal, Sphonasepal, Monkbot, Ying.l.xiong, YdJ, Catclaw666, JosephSlomka, Bender the Bot and Anonymous: 106 • SRGB Source: https://en.wikipedia.org/wiki/SRGB?oldid=763661617 Contributors: Damian Yerrick, Zundark, Leandrod, Yann, Julesd, Cherkash, Ehn, Charles Matthews, Gutza, Traal, Furrykef, Fibonacci, BenRG, Frazzydee, Hankwang, Pjedicke, Pengo, Grincho, Frencheigh, PenguiN42, Sam Hocevar, Ta bu shi da yu, Poccil, Vsmith, Smyth, Notinasnaid, ESkog, Spitzak, Army1987, Panjasan, Neonumbers, Danog, PAR, Wdfarmer, Gene Nygaard, NantonosAedui, Jacobolus, Ruud Koot, GregorB, Quiddity, Ian Dunster, Ian Pitchford, Sir- iusB, Bgwhite, Adoniscik, YurikBot, Wavelength, Gaius Cornelius, Pseudomonas, Marcus Cyron, Mipadi, Janke, Mysid, Mareklug, Ppanzini, BorgQueen, Femmina, KJBracey, DCEvoCE, Cmglee, SmackBot, Cryptor3, Mihai cartoaje, Davepape, KaiUwe, Unyoyega, Betacommand, Bugloaf, Nbarth, Pandora Xero, VMS Mosaic, Acdx, Charivari, Adam Nohejl, Deadcode, Stratadrake, Dicklyon, Dl2000, Chris319, Elharo, CmdrObot, Cxw, Thijs!bot, JAnDbot, DanRuderman, Sterrys, DrSeehas, Tercer, Nono64, BigrTex, SharkD, JensRex, ArdenD, Fylwind, Totsugeki, Dcouzin, Rebornsoldier, One half 3544, SieBot, RichardKirk, WurmWoode, Fnordware, PixelBot, Spike- ,Luckas-bot, Efa, Redbobblehat, Lijiaqigreat, Citation bot ,רנדום ,Toronto, Ogat, Skarebo, Emyr-d, Addbot, Olli Niemitalo, Zacao Martnym, Lainestl, E-t172, LMLB, Dcirovic, ZéroBot, Ida Shaw, DavidBrainard, Smgraphtech, Helpful Pixie Bot, Warmonk, Zyxwv99, CitationCleanerBot, Kakao 6e3 ra3a, Mntbat, Unixatwp, TCMemoire, Mattghali, Sizeofint, GreenC bot, Bender the Bot and Anonymous: 71 • HSL and HSV Source: https://en.wikipedia.org/wiki/HSL_and_HSV?oldid=763906888 Contributors: Tarquin, Heron, Michael Hardy, Ahoerstemeier, LittleDan, Crissov, Dysprosia, Furrykef, Samsara, Denelson83, Phil Boswell, Robbot, Noldoaran, Stewartadcock, An- cheta Wis, Smjg, DocWatson42, Artjt, Nayuki, Chameleon, Mckaysalisbury, Gadfium, Sven271, Pmanderson, Marc Mongenet, Tooki, Olivier Debre, Abdull, Kate, Dbaron, Smyth, Notinasnaid, Spitzak, Muraken, Rlaager, Ardric47, Minghong, Fatphil, !melquiades, Cibu- mamo, Ramvi, Cburnett, Raimondi~enwiki, VoluntarySlave, Mindmatrix, Ae-a, Jacobolus, MattGiuca, Trapolator, Umofomia, Waldir, DESiegel, Marudubshinki, BD2412, OMouse, Reisio, Rjwilmsi, Seidenstud, Salix alba, Aapo Laitinen, Skizatch, Colin Barrett, Tedder, Thecurran, Srleffler, Glenn L, Nehalem, Adoniscik, Wavelength, Hairy Dude, Hakeem.gadi, MrTroy, Narkstraws, Akrabbim, Attil- ios, SmackBot, FishSpeaker, Lawrencekhoo, KocjoBot~enwiki, Ohnoitsjamie, Mhss, Rst20xx, TimBentley, Konstable, VMS Mosaic, Mr Minchin, Loadmaster, Dicklyon, RichardF, Nialsh, Paul Foxworthy, NaBUru38, W1tgf, Stebulus, Feckhornet, Gremagor, Verdy p, MikeWard1701, RitKill, Keraunos, (3ucky(3all, Glennchan, Remi de, JAnDbot, Zzmonty, Samus uy, PaleAqua, Gavia immer, Magi- oladitis, Swpb, SwiftBot, David Eppstein, Drm310, MoA)gnome, R'n'B, Shadow Scythe of Strongbadia?!, SharkD, STBotD, Mike V, TWCarlson, Xienoph, Llorenzi, Nbeato, Normy rox, Pleasantville, Ttennebkram, Dprust, DavesPlanet, Krosto, Scorpion451, Halcionne, Svick, Capitalismojo, VanishedUser sdu9aya9fs787sads, ImageRemovalBot, ClueBot, The Thing That Should Not Be, EoGuy, Seaand- sky, Stlman, Humanengr, JKeck, WikHead, Lolsrus, Zinger0, J-vars, Addbot, Dark-metamortal, DOI bot, Fgnievinski, Mizukane203, Download, Superboy112233, Luckas-bot, Yobot, Adelpine, TaBOT-zerem, Aboalbiss, AnomieBOT, Angry bee, Lustiger seth, Materi- alscientist, Hullo exclamation mark, Kristjan.Jonasson, Vaxquis, FrescoBot, Citation bot 1, Maggyero, Ryan1965, LittleWink, Serols, Foobarnix, Full-date unlinking bot, Kallikanzarid, GustavLa, Hardtofindaname, Crackwitz, Dinamik-bot, Minimac, Sergey.volynkin, EmausBot, Adovid-Mila, Benhut1, Dcirovic, QuentinUK, Cm621, Wagino 20100516, Grayray, Ipsign, Serhatsakarya, FeatherPluma, ClueBot NG, Peter James, AlbertBickford, Mesophile, TheJ89, Escapepea, Rcorym15, BG19bot, Rdococ, Anubhab91, Steve11235, NotWith, Luizfrds, Maniandram01, HueSatLum, Rich S 10001, SaatchiCEO, Pintoch, 1fish2, Jessevanassen, Piotr Grochowski, ?land, DavRosen, Monkbot, YKanada, CliveMcCarthy, Bender the Bot and Anonymous: 214 • RGB color model Source: https://en.wikipedia.org/wiki/RGB_color_model?oldid=763067778 Contributors: Mav, Uriyan, Fnielsen, Christian List, Mjb, Heron, Branko, Bignose, Frecklefoot, Edward, Patrick, Michael Hardy, Menchi, Wapcaplet, Ixfd64, Iluvcapra, Alfio, Ellywa, Julesd, BAxelrod, Mxn, Arteitle, Hashar, Emperorbma, Crissov, Timwi, Dysprosia, Jay, Gutza, Tpbradbury, Omegatron, Wernher, Bevo, J D, Slawojarek, JorgeGG, Robbot, Hankwang, Noldoaran, RedWolf, Jleedev, Mfc, Alexwcovington, Kim Bruning, Bfinn, Gus Polly, Ecology2001, Thewikipedian, Chowbok, Zeimusu, Alex Cohn, Bodnotbod, Marc Mongenet, Quota, GreenReaper, Fanghong~enwiki, DmitryKo, Ornil, Poccil, Imroy, TedPavlic, RuiMalheiro, Notinasnaid, Quistnix, ZeroOne, Kjoonlee, Evice, Dkroll2, Bobo192, Emhoo~enwiki, Ardric47, Sam Korn, Alansohn, Jic, Patrick Bernier, NeoThermic, Pforret, Jaw959, Cburnett, NJM, Simet- rical, Jacobolus, Bbatsell, Crazysunshine, Btyner, Mandarax, Tslocum, Graham87, BD2412, Rjwilmsi, Tizio, Seidenstud, SudoMonas, Bruce1ee, Aapo Laitinen, Watcharakorn, Acetylene, Mirror Vax, Gurch, Yhelothur, Glenn L, Windharp, Chobot, Adoniscik, Kjlewis, YurikBot, Hyad, Fabartus, Kirill Lokshin, Gaius Cornelius, Wimt, Big Brother 1984, Daveswagon, SEWilcoBot, ScottyWZ, Voidxor, Killdevil, Bota47, Tonywalton, Ms2ger, Open2universe, Gtdp, Denisutku, MrTroy, BorgQueen, Petri Krohn, JoanneB, Mike1024, AG- Toth, Kungfuadam, SmackBot, Hydrogen Iodide, InvictaHOG, Renesis, Tommstein, Gilliam, Brianski, Durova, Chris the speller, Em- ufarmers, IIXII, Harris cone, VMS Mosaic, MichaelBillington, BurnDownBabylon, Hulmem, Loadmaster, Dicklyon, Saxbryn, PaulGS, Freelance Intellectual, Courcelles, ChrisCork, FleetCommand, Mattbr, Hucz, Zureks, W1tgf, Funnyfarmofdoom, Khatru2, Thijs!bot, John254, Bobblehead, Davidhorman, Philippe, The Fat Man Who Never Came Back, Nick Number, Aurabolt, AntiVandalBot, Widefox, JAnDbot, CosineKitty, Couchpotato99, Lzer, Jaysweet, VoABot II, Nikevich, Bilderbikkel, Aaron hoffmeyer, DerHexer, Ashishbhatna- gar72, Nopira, MartinBot, Auiow, Xumm1du, Arjun01, R'n'B, AlexiusHoratius, Nono64, Leyo, Wikiman232, Lilac Soul, Tntdj, SharkD, Jac20, Andy Johnston, Motine, KylieTastic, STBotD, RB972, Bonadea, Ja 62, Squids and Chips, Idioma-bot, Funandtrvl, VolkovBot, Chienlit, TXiKiBoT, Oshwah, Mercurywoodrose, Technopat, Rei-bot, Nl74, Rebornsoldier, Wiikipedian, Elphion, PDFbot, Ian Stra- chan, Pigslookfunny, Gona.eu, Ricardo Cancho Niemietz, Zachary8222, SieBot, Lucasbfrbot, Pi is 3.14159, Flyer22 Reborn, Taemyr, Oxymoron83, Bagatelle, Lisatwo, Airhogs777, Paulhiphop, Sanya3, Svick, SiefkinDR, Ken123BOT, ClueBot, AQJKU6GMN, Wurm- Woode, Mild Bill Hiccup, DragonBot, Matju2, Ybenharim, Muhandes, PollRokr, Vegetator, Orfest, InternetMeme, Saltrok, Ost316, Sil- 11.1. TEXT 185

vonenBot, Dubmill, Addbot, MrOllie, Jpchevreau~enwiki, Chzz, Doug youvan~enwiki, Lightbot, OlEnglish, Legobot, Luckas-bot, Yobot, Pcap, AnomieBOT, Materialscientist, Citation bot, LilHelpa, Xqbot, RibotBOT, Kristjan.Jonasson, Adavis444, Motsjo, A.amitkumar, Thehelpfulbot, Nagualdesign, Citation bot 1, I dream of horses, HRoestBot, Calmer Waters, RedBot, Serols, Thrissel, DixonDBot, Senior maloney, Vrenator, Sregister, Suffusion of Yellow, DARTH SIDIOUS 2, ArwinJ, Rayman60, Category Master, WikitanvirBot, Timde, GoingBatty, RA0808, Wikipelli, 15turnsm, DisplayGeek, Ὁ οἶστρος, U86774~enwiki, DR4K77, Bxj, Wagino 20100516, AndyThe- Grump, ClueBot NG, RaptorHunter, Verpies, Lyla1205, Frietjes, Widr, Helpful Pixie Bot, Alex5134, David.moreno72, Cyberbot II, Khazar2, TheRP113, Makecat-bot, TwoTwoHello, Jochen Burghardt, Brianwong1508, C5st4wr6ch, Marketply, Jodosma, Mcfadden- skyler, Derekdoth, Skr15081997, Avieshek, Yourmomho, Acvideo1, WiserX2020, Kjerish, Plateado91, Shashi Bhushan Yadav, Sheep- rain0627, Redolta, Qzd, GreenC bot, BlackVolt, Fmadd, Bender the Bot, Boötes, Shengguow and Anonymous: 335 • CMYK color model Source: https://en.wikipedia.org/wiki/CMYK_color_model?oldid=762956561 Contributors: AxelBoldt, Derek Ross, Mav, Bryan Derksen, Maury Markowitz, Heron, Kku, Liftarn, Wapcaplet, Ixfd64, Zeno Gantner, DropDeadGorgias, Mark Foskey, Mxn, Hashar, Emperorbma, Dcoetzee, Dysprosia, Morwen, Oaktree b, BenRG, Robbot, Hankwang, Jor, Seth Ilys, Xanzzibar, Mattflaschen, Un- free, Giftlite, DocWatson42, Rudolf 1922, Kim Bruning, Haeleth, Bfinn, Gilgamesh~enwiki, Eequor, Tooki, CoyneT, Fanghong~enwiki, Ta bu shi da yu, Rfl, Nido, Discospinster, Pak21, Andros 1337, Smyth, Notinasnaid, Pt, Susvolans, Pablo X, Bobo192, Drw25, Ardric47, Shehal, 4v4l0n42, Grigory Grin~enwiki, Pforret, Atlant, Snowolf, Cburnett, Ceyockey, Kbolino, Mindmatrix, Georgia guy, Daira Hop- wood, Jacobolus, Lincher, Vary, Oblivious, CalPaterson, Aapo Laitinen, Watcharakorn, FlaBot, Toresbe, Gurch, Bmicomp, Glenn L, YurikBot, Borgx, Antoin, Me and, Hede2000, Devnevyn, Josteinaj, LAW, Bozoid, Wangi, Crisco 1492, Mütze, MrTroy, GinaDana, Fpenteado, Eptin, Cmglee, SmackBot, Xaosflux, Gilliam, Skizzik, CKA3KA, Patriarch, Sullevon, DHN-bot~enwiki, Raymie, Can't sleep, clown will eat me, Joseph Crowe, Chlewbot, Fife Club, VMS Mosaic, Fvox13, Mystaker1, Mgiganteus1, Ckatz, CommKing, Beetstra, Dicklyon, BranStark, ChazYork, Jason.grossman, Newone, Tdmg, Tawkerbot2, FatalError, Huns0004, Jesse Viviano, RenamedUser2, Gogo Dodo, Quibik, Amspeck, Connectionfailure, PKT, Thijs!bot, Epbr123, BunnyHopz, RossO, Keraunos, Dtgriscom, (3ucky(3all, Netics, AntiVandalBot, Cinexero, KickahaOta, Prolog, Smartse, MER-C, Turbotape, Dricherby, VoABot II, NinjaSkitch, Brianmason, Nevit, Ashishbhatnagar72, Black Stripe, MartinBot, Tholly, Lilac Soul, Guirro, J.delanoy, Eliz81, NYCRuss, SharkD, WaltTFB, Rwessel, KylieTastic, Plindenbaum, Action Jackson IV, Mike V, Funandtrvl, Lights, Graphite Elbow, Jaredroach, Sklocke, Chienlit, Sroc, Nxavar, Rebornsoldier, Cuddlyable3, Jeeny, Seekue, Cluno, Serprex, SieBot, Parhamr, Ericksontc, Zero2ninE, Gunmetal Angel, Loren.wilton, Martarius, ClueBot, Bob1960evens, The Thing That Should Not Be, Arakunem, Txbangert, Dixieguy911, Bvlax2005, SunnySideOfStreet, Thingg, Spinoff, XLinkBot, IAMSOOUGLY, Ost316, The obs, Addbot, Superbleachbrothers, MrOllie, Avzit, Luckas-bot, 2D, Aboalbiss, AnomieBOT, Piano non troppo, Flewis, Chunheisiu, AL3X TH3 GR8, Ubcule, Shadowjams, Some standardized rigour, Prepressx, Mag- gyero, Gnepets, HRoestBot, Diomedea Exulans, DeeJay Antoine, Jschnur, Leak187, Gerda Arendt, Tuplanolla, Thrissel, Mitchell382, Devmanuel, Mikealx, EmausBot, WikitanvirBot, Westley Turner, U86774~enwiki, Brainflakes, Atcold, AVarchaeologist, ClueBot NG, Joelmuya, MelbourneStar, Robthepiper, Hofmic, Frietjes, Widr, Capsoul, Helpful Pixie Bot, Gauravjuvekar, Neøn, CitationCleanerBot, What a pro., Iankp, Markacastle, Divido, Viliam Furík, Massimopenzo, Evershortofinfinity, Dguzzo, Aviva11235, Gameaddict07, Prabal Mehrotra, Pariah24, Katemaylone, Cadders24, Yellowprinting, GreenC bot, Ffrodo8, Bender the Bot and Anonymous: 254 • Colorfulness Source: https://en.wikipedia.org/wiki/Colorfulness?oldid=761926184 Contributors: Rmhermen, Michael Hardy, Wap- caplet, Nikai, Robbot, Chealer, PBS, Lefty, Tagishsimon, Sonjaaa, CoyneT, Paul August, Night Gyr, Ylai, Spitzak, MisterSheik, Ben- jBot, Aude, Arcadian, Trevj, Varuna, Interiot, VivaEmilyDavies, Dan100, Jacobolus, Waldir, Rjwilmsi, Seraphimblade, Salix alba, Sr- leffler, Kri, Adoniscik, YurikBot, RobotE, Peter G Werner, Conscious, Casey56, RadioFan2 (usurped), Neilbeach, Welsh, RL0919, Zwobot, LeonardoRob0t, Tsiaojian lee, Roke, SmackBot, Eskimbot, Ohnoitsjamie, Jprg1966, MeekSaffron, Wmhawth, VMS Mo- saic, Radagast83, Natebw, DA3N, Dicklyon, Gproud, Thijs!bot, Keraunos, Escarbot, Alphachimpbot, JAnDbot, VoABot II, Wiki Raja, SharkD, VolkovBot, TallNapoleon, TXiKiBoT, MichaelStanford, SmileToday, Ratuliut, SieBot, Svick, Ken123BOT, ClueBot, Riskdoc, Green Heart 1985, Addbot, Morecambe1, Ettrig, Fryed-peach, Adelpine, Specious, Aboalbiss, AnomieBOT, Citation bot, Sims2uni, Gilo1969, Kevdave, Citation bot 1, Pinethicket, Full-date unlinking bot, Duoduoduo, RjwilmsiBot, EmausBot, Klbrain, Semolina Pilchard 67, ZéroBot, Frietjes, Uli Zappe, HappyLogolover2011, MerlIwBot, Helpful Pixie Bot, Doorknob747, BG19bot, Anbu121, BattyBot, Monkbot, DarthPseudonym, Bender the Bot and Anonymous: 51 • Grayscale Source: https://en.wikipedia.org/wiki/Grayscale?oldid=763235788 Contributors: Patrick, Delirium, Darkwind, Furrykef, Phil Boswell, Branddobbe, Zigger, Monedula, Lefty, Nabla, BenjBot, FirstPrinciples, Southen, Bobo192, Shlomital, Ahruman, Cburnett, Oleg Alexandrov, C3o, Marasmusine, Jacobolus, Emallove, Bhadani, Bgwhite, Adoniscik, Retodon8, RussBot, T, Newagelink, Petri Krohn, Alexandrov, SmackBot, Unschool, Eskimbot, Alsandro, Betacommand, Jerome Charles Potts, Sadads, OrphanBot, VMS Mosaic, Crboyer, Cybercobra, Test21~enwiki, Jaywubba1887, IronGargoyle, Loadmaster, Dicklyon, Neelix, ForrestCroce, Thijs!bot, Dfrg.msc, AntiVandalBot, Spartaz, Sterrys, CountingPine, Nevit, Dozen, Llorenzi, Bovineboy2008, Ricardo Cancho Niemietz, LarsHolmberg, Svick, Pinkadelica, ClueBot, GrandDrake, Bippo Ernesti, Blanchardb, DragonBot, PixelBot, Razorflame, DumZiBoT, Life of Riley, Ost316, NellieBly, Addbot, Queenmomcat, Olli Niemitalo, Fgnievinski, Shervinemami, MrOllie, Favonian, Baffle gab1978, Luckas-bot, Ciphers, Apollo, The Firewall, Xqbot, Agoubard, Bmclaughlin9, RedBot, Vrenator, Mean as custard, DASHBot, EmausBot, John of Reading, WikitanvirBot, ZéroBot, Westley Turner, Fixblor, LanoxxthShaddow, ClueBot NG, MelbourneStar, Helpful Pixie Bot, Dcmc- cue, Jecknowledge, ISewil, Dexbot, DavRosen, Manjhi the mountain man, Bender the Bot and Anonymous: 80 • Middle gray Source: https://en.wikipedia.org/wiki/Middle_gray?oldid=762396847 Contributors: Chaikney, Hooperbloob, Fawcett5, Ja- cobolus, The wub, Srleffler, Aspro, Neier, Chris the speller, Tomcool, Severoon, Trounce, Dicklyon, Artoonie, Alf photoman, Cpoynton, ,Yobot, Mononomic, Fortdj33, Codehydro, Lopifalko, Dcirovic, Modestginger, ClueBot NG ,רנדום ,Sybersitizen, Matma Rex, Addbot Helpful Pixie Bot, Bender the Bot and Anonymous: 8 • Gray card Source: https://en.wikipedia.org/wiki/Gray_card?oldid=740589720 Contributors: Imroy, Ashley Pomeroy, Velella, Authalic, Aspro, SmackBot, Trounce, Dicklyon, Thijs!bot, C.anguschandler, Hnc14, Burkhard.Plache, Lexort, Photodo, Traveler100, Fenke, Cry- walt, Perfect-Pixs, Addbot, Poco a poco, Yobot, Jhgarrison, Citation bot, Codehydro, NameIsRon, SteveWikiEdit, WikitanvirBot, Clue- Bot NG, Helpful Pixie Bot, Jacopo188, Makecat-bot, Zppix and Anonymous: 15 • List of monochrome and RGB palettes Source: https://en.wikipedia.org/wiki/List_of_monochrome_and_RGB_palettes?oldid=761546315 Contributors: Edward, Topbanana, Seajay, Jossi, Indrian, Oe1kenobi, Rjwilmsi, Quietust, NeonMerlin, Neonstz, DMahalko, Sangwine, SmackBot, Letdorf, Simpsons contributor, VMS Mosaic, Dinjiin, Dicklyon, Smiloid, Swpb, R'n'B, Squids and Chips, WinTakeAll, Ri- cardo Cancho Niemietz, Bitbut, Mac128, AzraelUK, ElGregos, SpellingBot, OlEnglish, Yobot, Eatmorchikin, MrBurns, Jim1138, J04n, FrescoBot, DrilBot, Abductive, ZephyrXero, John of Reading, AvicAWB, Shrewmania, Helpful Pixie Bot, Secarrie, Yourock17, 4throck, Rsjsouza, Dobie80, SoledadKabocha, Recollected, Kjerish, PiotrGrochowski000, Communal t, Chrome58, 24691358r and Anonymous: 77 186 CHAPTER 11. TEXT AND IMAGE SOURCES, CONTRIBUTORS, AND LICENSES

• Impossible color Source: https://en.wikipedia.org/wiki/Impossible_color?oldid=761583384 Contributors: Michael Hardy, IceKarma, Auric, Beland, Zowie, Welshie, Jpgordon, Anthony Appleyard, Drummstikk, Rjwilmsi, Koavf, XP1, Ysangkok, Chris Capoccia, Cate, Katieh5584, SmackBot, McGeddon, Xaosflux, OrangeDog, VMS Mosaic, WaldoJ, Dicklyon, Robnormal, NisseSthlm, Quintopia, JMatthews, Sobreira, Davidhorman, Gioto, Barek, Dekimasu, Metallaxis, Mmoople, Sroc, Lamro, Lova Falk, Zuchinni one, Spinningspark, Goustien, Jruderman, Wanderer32, Svick, Fuddle, Ratemonth, WurmWoode, Timberframe, Rhubbarb, RCalabraro, Wyatt915, Addbot, Boomur, Da5nsy, Dasanjos, Luckas-bot, Yobot, Vroo, MrBurns, AnomieBOT, AaRH, Citation bot, Acebulf, Aaron Kauppi, Jonkerz, Duoduoduo, Aoidh, Codehydro, Chipmunkdavis, ZéroBot, Itchesavvy, Mikechen, Mikhail Ryazanov, ClueBot NG, WryVendor, Crazymonkey1123 public, BG19bot, Tom Piantanida, Extoad, Tony Mach, Reatlas, Angruss, Melcous, Vinylscratchp0n3, Sizeofint, ʬʬ, Qzd, Maskhjdlkgjhd- flgkjdddd, Gulumeemee and Anonymous: 55

11.2 Images

• File:1-bit_grayscale.gif Source: https://upload.wikimedia.org/wikipedia/commons/7/7c/1-bit_grayscale.gif License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:12-bit_RGB_Cube.gif Source: https://upload.wikimedia.org/wikipedia/commons/0/0a/12-bit_RGB_Cube.gif License: CC BY- SA 4.0 Contributors: Own work Original artist: Kjerish • File:15-bit_RGB_Cube.gif Source: https://upload.wikimedia.org/wikipedia/commons/8/8a/15-bit_RGB_Cube.gif License: CC BY- SA 4.0 Contributors: Own work Original artist: Kjerish • File:16777216colors.png Source: https://upload.wikimedia.org/wikipedia/commons/e/e9/16777216colors.png License: CC BY-SA 2.5 Contributors: Own work Original artist: Marc Mongenet • File:18-bit_RGB_Cube.gif Source: https://upload.wikimedia.org/wikipedia/commons/e/e8/18-bit_RGB_Cube.gif License: CC BY- SA 4.0 Contributors: Own work Original artist: Kjerish • File:2-bit_grayscale.gif Source: https://upload.wikimedia.org/wikipedia/commons/e/e6/2-bit_grayscale.gif License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:3-bit_RGB_Cube.gif Source: https://upload.wikimedia.org/wikipedia/commons/f/fe/3-bit_RGB_Cube.gif License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:4-bit_grayscale.gif Source: https://upload.wikimedia.org/wikipedia/commons/b/ba/4-bit_grayscale.gif License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:59_-_Carthagène_-_Décembre_2008.JPG Source: https://upload.wikimedia.org/wikipedia/commons/9/94/59_-_Carthag%C3% A8ne_-_D%C3%A9cembre_2008.JPG License: CC BY-SA 3.0 Contributors: Own work Original artist: Martin St-Amant (S23678) • File:6-bit_RGB_Cube.gif Source: https://upload.wikimedia.org/wikipedia/commons/6/69/6-bit_RGB_Cube.gif License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:8-bit_grayscale.gif Source: https://upload.wikimedia.org/wikipedia/commons/c/c9/8-bit_grayscale.gif License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:9-bit_RGB_Cube.gif Source: https://upload.wikimedia.org/wikipedia/commons/8/8c/9-bit_RGB_Cube.gif License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:AICmezcla-total1.jpg Source: https://upload.wikimedia.org/wikipedia/commons/8/88/AICmezcla-total1.jpg License: CC BY-SA 3.0 Contributors: Own work Original artist: Caivano • File:AdditiveColor.svg Source: https://upload.wikimedia.org/wikipedia/commons/c/c2/AdditiveColor.svg License: Public domain Con- tributors: Transferred from en.wikipedia to Commons. Original artist: SharkD at English Wikipedia Later versions were uploaded by Jacobolus at en.wikipedia. • File:Additive_color_mixing.jpg Source: https://upload.wikimedia.org/wikipedia/commons/0/0b/Additive_color_mixing.jpg License: CC BY-SA 3.0 Contributors: Own work Original artist: Zátonyi Sándor, (ifj.) Fizped • File:Additive_color_mixing_simulated.png Source: https://upload.wikimedia.org/wikipedia/commons/2/2c/Additive_color_mixing_ simulated.png License: Public domain Contributors: Own work Original artist: Pko • File:Adobergb-in-cielab.png Source: https://upload.wikimedia.org/wikipedia/commons/3/33/Adobergb-in-cielab.png License: CC BY- SA 3.0 Contributors: Own work Original artist: Jacobolus • File:Ambox_important.svg Source: https://upload.wikimedia.org/wikipedia/commons/b/b4/Ambox_important.svg License: Public domain Contributors: Own work, based oﬀ of Image:Ambox scales.svg Original artist: Dsmurat (talk · contribs) • File:AmstradCPC_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/a/a1/AmstradCPC_palette.png License: Pub- lic domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:AmstradCPC_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/b/b0/AmstradCPC_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:AmstradCPC_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/9/9f/AmstradCPC_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:BYR_color_wheel.svg Source: https://upload.wikimedia.org/wikipedia/commons/3/38/BYR_color_wheel.svg License: CC-BY- SA-3.0 Contributors: Transferred from en.wikipedia to Commons. Transfer was stated to be made by User:nopira. Original artist: The original uploader was Sakurambo at English Wikipedia • File:Barns_grand_tetons.jpg Source: https://upload.wikimedia.org/wikipedia/commons/d/d0/Barns_grand_tetons.jpg License: Public domain Contributors: PD Photo, http://pdphoto.org/PictureDetail.php?mat=pdef&pg=8145 Original artist: Jon Sullivan, PD Photo. 11.2. IMAGES 187

• File:Bayer_pattern_on_sensor.svg Source: https://upload.wikimedia.org/wikipedia/commons/3/37/Bayer_pattern_on_sensor.svg Li- cense: CC-BY-SA-3.0 Contributors: This vector image was created with Inkscape. Original artist: en:User:Cburnett • File:Beyoglu_4671_tricolor.png Source: https://upload.wikimedia.org/wikipedia/commons/3/33/Beyoglu_4671_tricolor.png License: CC BY-SA 3.0 Contributors: This ﬁle was derived from Beyoglu 4671.jpg: Original artist: Beyoglu_4671.jpg: Nevit Dilmen • File:Bezold_Farbentafel_1874.jpg Source: https://upload.wikimedia.org/wikipedia/commons/a/a9/Bezold_Farbentafel_1874.jpg Li- cense: Public domain Contributors: Die Farbenlehre im Hinblick auf Kunst und Kunstgewerbe. Braunschweig: Verlag von George West- ermann, ﬁgure online at uni-mannheim.de Original artist: Wilhelm von Bezhold • File:Bilevel_1bit_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/6/66/Bilevel_1bit_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Bilevel_1bit_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/6/69/Bilevel_1bit_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Bilevel_1bit_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/8/8e/Bilevel_1bit_palette_sample_ image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Bilevel_1bit_palette_sample_image_-_gimp_dithered.png Source: https://upload.wikimedia.org/wikipedia/commons/1/19/Bilevel_ 1bit_palette_sample_image_-_gimp_dithered.png License: Public domain Contributors: • RGB_24bits_palette_sample_image.jpg Original artist: RGB_24bits_palette_sample_image.jpg: Ricardo Cancho Niemietz (talk) • File:Black-white-1px-checkers.svg Source: https://upload.wikimedia.org/wikipedia/commons/a/a4/Black-white-1px-checkers.svg Li- cense: CC BY-SA 4.0 Contributors: Own work (based on SVG source code of ) Original artist: Codehydro • File:Boutet_1708_color_circles.jpg Source: https://upload.wikimedia.org/wikipedia/commons/b/b2/Boutet_1708_color_circles.jpg Li- cense: Public domain Contributors: Traité de la peinture en mignature (The Hague, 1708), reproduced in The Creation of Color in Eighteenth-Century Europe Original artist: C. B. (probably Claude Boutet) • File:CIE1931simple.png Source: https://upload.wikimedia.org/wikipedia/commons/6/67/CIE1931simple.png License: CC-BY-SA-3.0 Contributors: ? Original artist: ? • File:CIE1931xy_blank.svg Source: https://upload.wikimedia.org/wikipedia/commons/3/3b/CIE1931xy_blank.svg License: Public domain Contributors: File:CIExy1931.svg Original artist: BenRG • File:CIE1931xy_gamut_comparison.svg Source: https://upload.wikimedia.org/wikipedia/commons/1/1e/CIE1931xy_gamut_comparison. svg License: CC BY-SA 3.0 Contributors: http://commons.wikimedia.org/wiki/File:CIE1931xy_blank.svg Original artist: BenRG and cmglee • File:CIE_1976_UCS.png Source: https://upload.wikimedia.org/wikipedia/commons/8/83/CIE_1976_UCS.png License: Public domain Contributors: Own work Original artist: Adoniscik • File:CIExy1931.png Source: https://upload.wikimedia.org/wikipedia/commons/b/b0/CIExy1931.png License: Public domain Contrib- utors: Own work Original artist: User:PAR • File:CIExy1931_ProPhoto.svg Source: https://upload.wikimedia.org/wikipedia/commons/e/eb/CIExy1931_ProPhoto.svg License: Pub- lic domain Contributors: en:File:CIExy1931 ProPhoto.png Original artist: Fred the Oyster • File:CIExy1931_fixed.svg Source: https://upload.wikimedia.org/wikipedia/commons/f/f3/CIExy1931_fixed.svg License: CC-BY-SA- 3.0 Contributors: • CIExy1931.svg Original artist: CIExy1931.svg: Sakurambo • File:CIExy1931_sRGB_gamut_D65.png Source: https://upload.wikimedia.org/wikipedia/commons/0/08/CIExy1931_sRGB_gamut_ D65.png License: CC-BY-SA-3.0 Contributors: Transferred from en.wikipedia to Commons by aboalbiss. Original artist: The original uploader was Dicklyon at English Wikipedia • File:CMYK_Spectrum_printed_paper.pdf Source: https://upload.wikimedia.org/wikipedia/en/c/cf/CMYK_Spectrum_printed_paper. pdf License: CC-BY-SA-3.0 Contributors: ? Original artist: ? • File:CMYK_color_swatches.svg Source: https://upload.wikimedia.org/wikipedia/commons/4/4c/CMYK_color_swatches.svg License: CC BY-SA 2.5 Contributors: ? Original artist: ? • File:CMYK_screen_angles.svg Source: https://upload.wikimedia.org/wikipedia/commons/3/35/CMYK_screen_angles.svg License: CC BY-SA 3.0 Contributors: Own work Original artist: Cmglee • File:CMYK_separation_–_maximum_black.jpg Source: https://upload.wikimedia.org/wikipedia/commons/2/2e/CMYK_separation_ %E2%80%93_maximum_black.jpg License: GFDL Contributors: CMYK separation – maximum black Original artist: Jon Sullivan, PD Photo; This color separation by Jacob Rus • File:CMYK_separation_–_no_black.jpg Source: https://upload.wikimedia.org/wikipedia/commons/f/f0/CMYK_separation_%E2% 80%93_no_black.jpg License: GFDL Contributors: Original photograph from PD Photo, http://pdphoto.org/PictureDetail.php?mat= pdef&pg=8145 Original artist: Jon Sullivan, PD Photo; This color separation by Jacob Rus 188 CHAPTER 11. TEXT AND IMAGE SOURCES, CONTRIBUTORS, AND LICENSES

• File:CRT_color_enhanced.png Source: https://upload.wikimedia.org/wikipedia/commons/9/9b/CRT_color_enhanced.png License: CC- BY-SA-3.0 Contributors: source code and basic design of Image:CRT color.png by Søren Peo Pedersen. Own render with minor fixes and Photoshop enhancements. Original artist: grmᵣ (homeᵢᵢ) • File:CRT_phosphors.png Source: https://upload.wikimedia.org/wikipedia/commons/2/29/CRT_phosphors.png License: CC-BY-SA- 3.0 Contributors: Transfered from en.wikipedia Transfer was stated to be made by User:Nopira. Original artist: Original uploader was Deglr6328 at en.wikipedia • File:Canon_S520_ink_jet_printer_-_opened_(cropped).jpg Source: https://upload.wikimedia.org/wikipedia/commons/8/85/Canon_ S520_ink_jet_printer_-_opened_%28cropped%29.jpg License: CC BY-SA 2.5 Contributors: Own work Original artist: André Karwath aka Aka • File:Castel_L'Optique_des_couleurs_1740.jpg Source: https://upload.wikimedia.org/wikipedia/commons/4/47/Castel_L%27Optique_ des_couleurs_1740.jpg License: Public domain Contributors: L'Optique des couleurs (Paris, 1740), p. 414, reproduced in The Creation of Color in Eighteenth-Century Europe Original artist: Louis-Bertrand Castel • File:Chimerical-color-demo.svg Source: https://upload.wikimedia.org/wikipedia/commons/5/56/Chimerical-color-demo.svg License: CC BY-SA 3.0 Contributors: I produced it in Inkscape Previously published: NA Original artist: Zowie • File:Cie_Chart_with_sRGB_gamut_by_spigget.png Source: https://upload.wikimedia.org/wikipedia/commons/6/60/Cie_Chart_with_ sRGB_gamut_by_spigget.png License: CC BY-SA 3.0 Contributors: Own work Original artist: Spigget • File:Color_diagram_Charles_Hayter.jpg Source: https://upload.wikimedia.org/wikipedia/commons/1/15/Color_diagram_Charles_ Hayter.jpg License: Public domain Contributors: From: Charles Hayter published A New Practical Treatise on the Three Primitive Colours Assumed as a Perfect System of Rudimentary Information (London 1826), in which he described how all colours could be obtained from just three. Original artist: Charles Hayter • File:Color_perception.svg Source: https://upload.wikimedia.org/wikipedia/commons/4/4c/Color_perception.svg License: Public domain Contributors: Own work Original artist: Wyatt915 • File:Color_star-en_(tertiary_names).svg Source: https://upload.wikimedia.org/wikipedia/commons/8/8c/Color_star-en_%28tertiary_ names%29.svg License: CC BY-SA 4.0 Contributors: Own work Original artist: Kwamikagami • File:Colorcircle.png Source: https://upload.wikimedia.org/wikipedia/en/4/46/Colorcircle.png License: Cc-by-sa-3.0 Contributors: ? Original artist: ? • File:Colores_aditivos.png Source: https://upload.wikimedia.org/wikipedia/commons/5/55/Colores_aditivos.png License: CC BY-SA 4.0 Contributors: Own work Original artist: Maulucioni • File:Colorspace.png Source: https://upload.wikimedia.org/wikipedia/commons/3/37/Colorspace.png License: CC BY 2.5 Contributors: Transferred from en.wikipedia to Commons by aboalbiss. Original artist: The original uploader was Cpesacreta at English Wikipedia • File:Colour_shift.jpg Source: https://upload.wikimedia.org/wikipedia/commons/9/95/Colour_shift.jpg License: CC BY-SA 4.0 Con- tributors: Own work http://www.poeticmind.co.uk/research/organising-information-colours-design-tips/ Original artist: 39james • File:Colouring_pencils.jpg Source: https://upload.wikimedia.org/wikipedia/commons/b/b1/Colouring_pencils.jpg License: CC BY- SA 3.0 Contributors: Own work Original artist: MichaelMaggs • File:Commons-logo.svg Source: https://upload.wikimedia.org/wikipedia/en/4/4a/Commons-logo.svg License: PD Contributors: ? Orig- inal artist: ? • File:Cones_SMJ2_E.svg Source: https://upload.wikimedia.org/wikipedia/commons/1/1e/Cones_SMJ2_E.svg License: CC BY-SA 3.0 Contributors: Based on Dicklyon’s PNG version, itself based on data from Stockman, MacLeod & Johnson (1993) Journal of the Opti- cal Society of America A, 10, 2491-2521d http://psy.ucsd.edu/~{}dmacleod/publications/61StockmanMacLeodJohnson1993.pdf (log E human cone response, via http://www.cvrl.org/database/text/cones/smj2.htm) Original artist: Vanessaezekowitz at en.wikipedia / Later version uploaded by BenRG. • File:Duhauron1877.jpg Source: https://upload.wikimedia.org/wikipedia/commons/0/08/Duhauron1877.jpg License: Public domain Contributors: Unknown Original artist: Louis Ducos du Hauron (1837 – 1920) • File:Edit-clear.svg Source: https://upload.wikimedia.org/wikipedia/en/f/f2/Edit-clear.svg License: Public domain Contributors: The Tango! Desktop Project. Original artist: The people from the Tango! project. And according to the meta-data in the file, specifically: “Andreas Nilsson, and Jakub Steiner (although minimally).” • File:Example_of_LAB_color_enhancement.jpg Source: https://upload.wikimedia.org/wikipedia/commons/f/f3/Example_of_LAB_ color_enhancement.jpg License: CC0 Contributors: Own work Original artist: Ll1324 • File:Excitation_Purity.svg Source: https://upload.wikimedia.org/wikipedia/commons/9/96/Excitation_Purity.svg License: CC-BY-SA- 3.0 Contributors: Created by me, derived from Image:CIExy1931.svg Original artist: adoniscik • File:Fire-breather_601_Luma_Y'.jpg Source: https://upload.wikimedia.org/wikipedia/commons/2/28/Fire-breather_601_Luma_Y% 27.jpg License: CC-BY-SA-3.0 Contributors: Fire_breathing_2_Luc_Viatour.jpg Original artist: Fire_breathing_2_Luc_Viatour.jpg: Luc Viatour; various “lightness” components extracted by jacobolus • File:Fire-breather_CIELAB_L*.jpg Source: https://upload.wikimedia.org/wikipedia/commons/e/e5/Fire-breather_CIELAB_L%2A. jpg License: CC-BY-SA-3.0 Contributors: Fire_breathing_2_Luc_Viatour.jpg Original artist: Fire_breathing_2_Luc_Viatour.jpg: Luc Viatour; various “lightness” components extracted by jacobolus • File:Fire-breather_HSL_L.jpg Source: https://upload.wikimedia.org/wikipedia/commons/0/06/Fire-breather_HSL_L.jpg License: CC- BY-SA-3.0 Contributors: Fire_breathing_2_Luc_Viatour.jpg Original artist: Fire_breathing_2_Luc_Viatour.jpg: Luc Viatour; various “lightness” components extracted by jacobolus • File:Fire-breather_HSV_V.jpg Source: https://upload.wikimedia.org/wikipedia/commons/4/43/Fire-breather_HSV_V.jpg License: CC- BY-SA-3.0 Contributors: Fire_breathing_2_Luc_Viatour.jpg Original artist: Fire_breathing_2_Luc_Viatour.jpg: Luc Viatour; various “lightness” components extracted by jacobolus 11.2. 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• File:Fire-breather_mean(R,G,B)_I.jpg Source: https://upload.wikimedia.org/wikipedia/commons/f/fe/Fire-breather_mean%28R% 2CG%2CB%29_I.jpg License: CC-BY-SA-3.0 Contributors: Fire_breathing_2_Luc_Viatour.jpg Original artist: Fire_breathing_2_Luc_Viatour.jpg: Luc Viatour; various “lightness” components extracted by jacobolus • File:Fire_breathing_2_Luc_Viatour.jpg Source: https://upload.wikimedia.org/wikipedia/commons/0/02/Fire_breathing_2_Luc_Viatour. jpg License: CC-BY-SA-3.0 Contributors: Own work www.lucnix.be Original artist: Luc Viatour • File:Folder_Hexagonal_Icon.svg Source: https://upload.wikimedia.org/wikipedia/en/4/48/Folder_Hexagonal_Icon.svg License: Cc- by-sa-3.0 Contributors: ? Original artist: ? • File:GB_16bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/7/77/GB_16bits_palette_color_ test_chart.png License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:GB_16bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/3/3d/GB_16bits_palette_sample_ image.png License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:Goethe,_Farbenkreis_zur_Symbolisierung_des_menschlichen_Geistes-_und_Seelenlebens,_1809.jpg Source: https://upload. wikimedia.org/wikipedia/commons/2/23/Goethe%2C_Farbenkreis_zur_Symbolisierung_des_menschlichen_Geistes-_und_Seelenlebens% 2C_1809.jpg License: Public domain Contributors: Transferred from de.wikipedia to Commons by Andrei Stroe using CommonsHelper. Original artist: The original uploader was Luestling at German Wikipedia • File:Goethe-Prism-FigI.jpg Source: https://upload.wikimedia.org/wikipedia/en/0/00/Goethe-Prism-FigI.jpg License: Cc-by-sa-3.0 Contributors: ? Original artist: ? • File:Goethe-colour.ogg Source: https://upload.wikimedia.org/wikipedia/commons/c/c0/Goethe-colour.ogg License: CC-BY-SA-3.0 Contributors: recorded by me (user: johnrpenner), toronto island, June 1, 2008. freely donated to wikipedia under the GFDL license. Original artist: The original uploader was Johnrpenner at English Wikipedia • File:Goethe_Schiller_Die_Temperamentenrose.jpg Source: https://upload.wikimedia.org/wikipedia/commons/8/82/Goethe_Schiller_ Die_Temperamentenrose.jpg License: Public domain Contributors: “Biedermeier”, Die Erfindung der Einfachheit. Katalog. Hatje Cantz Verlag Ostfildern 2006. ISBN 978-37757-1795-3 Original artist: Johann Wolfgang von Goethe, Friedrich Schiller • File:Graukarte.svg Source: https://upload.wikimedia.org/wikipedia/commons/e/e5/Graukarte.svg License: GPL Contributors: Own work Original artist: Apostoloff • File:Grayscale_2bit_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/3/35/Grayscale_2bit_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Grayscale_2bit_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/7/79/Grayscale_2bit_ palette_color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Can- cho Niemietz (talk) • File:Grayscale_2bit_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/8/8f/Grayscale_2bit_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Grayscale_2bit_palette_sample_image_-_gimp_dithered.png Source: https://upload.wikimedia.org/wikipedia/commons/a/a8/ Grayscale_2bit_palette_sample_image_-_gimp_dithered.png License: Public domain Contributors: • RGB_24bits_palette_sample_image.jpg Original artist: RGB_24bits_palette_sample_image.jpg: Ricardo Cancho Niemietz (talk) • File:Grayscale_4bit_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/b/bd/Grayscale_4bit_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Grayscale_4bit_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/2/27/Grayscale_4bit_ palette_color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Can- cho Niemietz (talk) • File:Grayscale_4bit_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/e/e4/Grayscale_4bit_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Grayscale_4bit_palette_sample_image_-_gimp_dithered.png Source: https://upload.wikimedia.org/wikipedia/commons/f/f1/ Grayscale_4bit_palette_sample_image_-_gimp_dithered.png License: Public domain Contributors: • RGB_24bits_palette_sample_image.jpg Original artist: RGB_24bits_palette_sample_image.jpg: Ricardo Cancho Niemietz (talk) • File:Grayscale_8bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/b/be/Grayscale_8bits_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Grayscale_8bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/1/13/Grayscale_8bits_ palette_color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Grayscale_8bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/f/fa/Grayscale_8bits_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Greenblue.png Source: https://upload.wikimedia.org/wikipedia/commons/2/2b/Greenblue.png License: CC BY-SA 4.0 Contribu- tors: Own work Original artist: Kjerish • File:Gretag-Macbeth_ColorChecker.jpg Source: https://upload.wikimedia.org/wikipedia/commons/a/ad/Gretag-Macbeth_ColorChecker. jpg License: Public domain Contributors: shot it myself with a Foveon X3 prototype camera Original artist: Richard F. Lyon Subject: • File:HSL-HSV_hue_and_chroma.svg Source: https://upload.wikimedia.org/wikipedia/commons/5/52/HSL-HSV_hue_and_chroma. svg License: CC BY-SA 3.0 Contributors: Own work Original artist: Jacob Rus • File:HSL_color_solid_cylinder_alpha_lowgamma.png Source: https://upload.wikimedia.org/wikipedia/commons/c/cb/HSL_color_ solid_cylinder_alpha_lowgamma.png License: CC BY-SA 3.0 Contributors: 190 CHAPTER 11. TEXT AND IMAGE SOURCES, CONTRIBUTORS, AND LICENSES

• HSL_color_solid_cylinder.png Original artist: HSL_color_solid_cylinder.png: SharkD • File:HSL_color_solid_dblcone_chroma_gray.png Source: https://upload.wikimedia.org/wikipedia/commons/b/b3/HSL_color_solid_ dblcone_chroma_gray.png License: CC BY-SA 3.0 Contributors: • Hcl-hcv_models.svg Original artist: Hcl-hcv_models.svg: Jacob Rus • File:HSV-RGB-comparison.svg Source: https://upload.wikimedia.org/wikipedia/commons/5/5d/HSV-RGB-comparison.svg License: CC-BY-SA-3.0 Contributors: en:Image:HSV_RGB_Comparison.svg Original artist: en:user:Goffrie • File:HSV_color_solid_cone_chroma_gray.png Source: https://upload.wikimedia.org/wikipedia/commons/0/00/HSV_color_solid_cone_ chroma_gray.png License: CC BY-SA 3.0 Contributors: • Hcl-hcv_models.svg Original artist: Hcl-hcv_models.svg: Jacob Rus • File:HSV_color_solid_cylinder_alpha_lowgamma.png Source: https://upload.wikimedia.org/wikipedia/commons/0/0d/HSV_color_ solid_cylinder_alpha_lowgamma.png License: CC BY-SA 3.0 Contributors: • HSV_color_solid_cylinder.png Original artist: HSV_color_solid_cylinder.png: SharkD • File:Halftoningcolor.svg Source: https://upload.wikimedia.org/wikipedia/commons/e/ef/Halftoningcolor.svg License: Public domain Contributors: • Halftoningcolor.png Original artist: • derivative work: Pbroks13 (talk) • File:Hawaii-turtle_hue_shifted.jpg Source: https://upload.wikimedia.org/wikipedia/commons/7/7e/Hawaii-turtle_hue_shifted.jpg Li- cense: CC-BY-SA-3.0 Contributors: Hawaii turtle 2.JPG Original artist: Hawaii turtle 2.JPG: Brocken Inaglory, retouched by Keta; hue shifted variant by jacobolus • File:Hawaii-turtle_hue_shifted_with_constant_L*.jpg Source: https://upload.wikimedia.org/wikipedia/commons/7/75/Hawaii-turtle_ hue_shifted_with_constant_L%2A.jpg License: CC-BY-SA-3.0 Contributors: Hawaii turtle 2.JPG Original artist: Hawaii turtle 2.JPG: Brocken Inaglory, retouched by Keta; hue shifted variant by jacobolus • File:Hawaii_turtle_2.JPG Source: https://upload.wikimedia.org/wikipedia/commons/b/bb/Hawaii_turtle_2.JPG License: CC-BY-SA- 3.0 Contributors: Photograph by Brocken Inaglory, edited by Keta Original artist: Brocken Inaglory • File:Hsi_saturation-intensity_slices.svg Source: https://upload.wikimedia.org/wikipedia/commons/5/55/Hsi_saturation-intensity_slices. svg License: CC BY-SA 3.0 Contributors: Own work Original artist: Jacob Rus • File:Hsl-and-hsv.svg Source: https://upload.wikimedia.org/wikipedia/commons/a/ac/Hsl-and-hsv.svg License: CC BY-SA 3.0 Contrib- utors: Own work Original artist: Jacob Rus • File:Hsl-hsv-colorpickers.svg Source: https://upload.wikimedia.org/wikipedia/en/e/ea/Hsl-hsv-colorpickers.svg License: Fair use Con- tributors: Several come from GUIdebook, others garnered from web image searches. 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Original artist: LaserSoft Imaging The original uploader was Sven Boisen at German Wikipedia • File:Impossible_Colors,_Blue_and_Yellow,_for_3dTV.png Source: https://upload.wikimedia.org/wikipedia/commons/8/8f/Impossible_ Colors%2C_Blue_and_Yellow%2C_for_3dTV.png License: Public domain Contributors: http://en.wikipedia.org/wiki/File:Yelue.svg Original artist: Wyatt915 • File:J_C_Maxwell_with_top.jpg Source: https://upload.wikimedia.org/wikipedia/commons/a/a7/J_C_Maxwell_with_top.jpg License: Public domain Contributors: ? 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• File:MSX2_Screen8_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/7/76/MSX2_Screen8_ palette_color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:MSX2_Screen8_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/6/6f/MSX2_Screen8_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:Manweissabgleich.jpg Source: https://upload.wikimedia.org/wikipedia/commons/a/a9/Manweissabgleich.jpg License: Public domain Contributors: Own work Original artist: Christian H. • File:Munsell_color_sphere.png Source: https://upload.wikimedia.org/wikipedia/commons/3/35/Munsell_color_sphere.png License: Pub- lic domain Contributors: A Color Notation Original artist: Albert Henry Munsell • File:NIEdot367.jpg Source: https://upload.wikimedia.org/wikipedia/commons/b/b6/NIEdot367.jpg License: Public domain Contribu- tors: New International Encyclopedia Original artist: Dodd, Mead and Company • File:Nasir-al_molk_-1.jpg Source: https://upload.wikimedia.org/wikipedia/commons/8/80/Nasir-al_molk_-1.jpg License: CC BY-SA 4.0 Contributors: Own work Original artist: Ayyoubsabawiki • File:Newton’{}s_colour_circle.png Source: https://upload.wikimedia.org/wikipedia/commons/0/0a/Newton%27s_colour_circle.png Li- cense: Public domain Contributors: Opticks. 1704, from Book I, Part II, Proposition VI, Problem 2. 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See this page. Original artist: ? • File:Palette_of_125_main_colors_with_RGB_components_divisible_by_64.gif Source: https://upload.wikimedia.org/wikipedia/commons/ 2/2e/Palette_of_125_main_colors_with_RGB_components_divisible_by_64.gif License: CC BY-SA 3.0 Contributors: Own work Orig- inal artist: Jochen Burghardt • File:Portal-puzzle.svg Source: https://upload.wikimedia.org/wikipedia/en/f/fd/Portal-puzzle.svg License: Public domain Contributors: ? Original artist: ? • File:Prism-orientation-of-light-dark-boundary.gif Source: https://upload.wikimedia.org/wikipedia/en/0/04/Prism-orientation-of-light-dark-boundary. gif License: Cc-by-sa-3.0 Contributors: ? Original artist: ? • File:Prisma-goethe.gif Source: https://upload.wikimedia.org/wikipedia/en/f/f8/Prisma-goethe.gif License: Cc-by-sa-3.0 Contributors: ? 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Based on Image:Question book.png created by User:Equazcion Original artist: Tkgd2007 • File:RBG_color_wheel.svg Source: https://upload.wikimedia.org/wikipedia/commons/a/ab/RBG_color_wheel.svg License: CC BY- SA 3.0 Contributors: Own work (Original text: self-made) Original artist: DanPMK • File:RB_16bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/5/50/RB_16bits_palette_color_ test_chart.png License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:RB_16bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/f/f2/RB_16bits_palette_sample_ image.png License: CC BY-SA 4.0 Contributors: Own work Original artist: Kjerish • File:RGBI_4bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/8/84/RGBI_4bits_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGBI_4bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/a/a8/RGBI_4bits_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGBI_4bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/1/1f/RGBI_4bits_palette_sample_ image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_12bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/4/47/RGB_12bits_palette.png License: Pub- lic domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) 192 CHAPTER 11. 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• File:RGB_12bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/d/d7/RGB_12bits_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_12bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/5/56/RGB_12bits_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_15bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/5/59/RGB_15bits_palette.png License: Pub- lic domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_15bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/b/bc/RGB_15bits_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_15bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/a/a8/RGB_15bits_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_16bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/d/d1/RGB_16bits_palette.png License: Pub- lic domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_16bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/e/e0/RGB_16bits_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_16bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/6/67/RGB_16bits_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_18bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/3/34/RGB_18bits_palette.png License: Pub- lic domain Contributors: recompression of an identic PD image in the English Wikipedia Originally uploaded 01:49, 2 February 2008 UTC (log) by Ricardo Cancho Niemietz (talk • contribs) to en:Wikipedia. Original artist: Ricardo Cancho Niemietz • File:RGB_18bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/d/dc/RGB_18bits_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_18bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/d/d9/RGB_18bits_palette_ sample_image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_R0.png Source: https://upload.wikimedia.org/wikipedia/commons/9/92/RGB_24bits_palette_R0.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_R170.png Source: https://upload.wikimedia.org/wikipedia/commons/9/91/RGB_24bits_palette_R170.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_R255.png Source: https://upload.wikimedia.org/wikipedia/commons/6/6c/RGB_24bits_palette_R255.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_R85.png Source: https://upload.wikimedia.org/wikipedia/commons/2/2a/RGB_24bits_palette_R85.png Li- cense: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/b/b8/RGB_24bits_palette_ color_test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_color_test_chart_-_1-bit_dithered.png Source: https://upload.wikimedia.org/wikipedia/commons/4/45/RGB_ 24bits_palette_color_test_chart_-_1-bit_dithered.png License: Public domain Contributors: • RGB_24bits_palette_color_test_chart.png Original artist: RGB_24bits_palette_color_test_chart.png: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_color_test_chart_-_2-bit_dithered.png Source: https://upload.wikimedia.org/wikipedia/commons/e/ee/RGB_ 24bits_palette_color_test_chart_-_2-bit_dithered.png License: Public domain Contributors: • RGB_24bits_palette_color_test_chart.png Original artist: RGB_24bits_palette_color_test_chart.png: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_color_test_chart_-_3-bit_RGB_dithered.png Source: https://upload.wikimedia.org/wikipedia/commons/ 5/59/RGB_24bits_palette_color_test_chart_-_3-bit_RGB_dithered.png License: Public domain Contributors: • RGB_24bits_palette_color_test_chart.png Original artist: RGB_24bits_palette_color_test_chart.png: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_color_test_chart_-_4-bit_gray_dithered.png Source: https://upload.wikimedia.org/wikipedia/commons/ 8/8f/RGB_24bits_palette_color_test_chart_-_4-bit_gray_dithered.png License: Public domain Contributors: • RGB_24bits_palette_color_test_chart.png Original artist: RGB_24bits_palette_color_test_chart.png: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_sample_image.jpg Source: https://upload.wikimedia.org/wikipedia/commons/d/d7/RGB_24bits_palette_ sample_image.jpg License: Public domain Contributors: self-made adaptation of a common Wikipedia image (Image:Parrot.red.macaw. 1.arp.750pix.jpg). Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_24bits_palette_sample_image_-_3-bit_RGB.png Source: https://upload.wikimedia.org/wikipedia/commons/7/79/RGB_ 24bits_palette_sample_image_-_3-bit_RGB.png License: Public domain Contributors: • RGB_24bits_palette_sample_image.jpg Original artist: RGB_24bits_palette_sample_image.jpg: Ricardo Cancho Niemietz (talk) • File:RGB_3bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/e/ed/RGB_3bits_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) 11.2. IMAGES 193

• File:RGB_3bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/8/88/RGB_3bits_palette_color_ test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_3bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/3/3b/RGB_3bits_palette_sample_ image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_6bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/3/3d/RGB_6bits_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_6bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/b/bf/RGB_6bits_palette_color_ test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_6bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/1/13/RGB_6bits_palette_sample_ image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_9bits_palette.png Source: https://upload.wikimedia.org/wikipedia/commons/a/a8/RGB_9bits_palette.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_9bits_palette_color_test_chart.png Source: https://upload.wikimedia.org/wikipedia/commons/c/c9/RGB_9bits_palette_color_ test_chart.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_9bits_palette_sample_image.png Source: https://upload.wikimedia.org/wikipedia/commons/a/ad/RGB_9bits_palette_sample_ image.png License: Public domain Contributors: Own work (Original text: self-made) Original artist: Ricardo Cancho Niemietz (talk) • File:RGB_Cube_Show_lowgamma_cutout_a.png Source: https://upload.wikimedia.org/wikipedia/commons/0/05/RGB_Cube_Show_ lowgamma_cutout_a.png License: CC BY-SA 3.0 Contributors: • RGB_farbwuerfel.jpg Original artist: RGB_farbwuerfel.jpg: Horst Frank • File:RGB_Cube_Show_lowgamma_cutout_b.png Source: https://upload.wikimedia.org/wikipedia/commons/8/83/RGB_Cube_Show_ lowgamma_cutout_b.png License: CC BY-SA 3.0 Contributors: • RGB_farbwuerfel.jpg Original artist: RGB_farbwuerfel.jpg: Horst Frank • File:RGB_and_CMYK_comparison.png Source: https://upload.wikimedia.org/wikipedia/commons/1/1b/RGB_and_CMYK_comparison. png License: Public domain Contributors: • Made in Photoshop. Original was also made in Photoshop in 2003. 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Arthur H. 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TIFF ﬁle from LOC Original artist: Sergey Prokudin-Gorsky • File:Runge_Farbenkugel.jpg Source: https://upload.wikimedia.org/wikipedia/commons/9/94/Runge_Farbenkugel.jpg License: Pub- lic domain Contributors: Philipp Otto Runge (1810). Farben-Kugel oder Construction des Verhältnisses aller Mischungen der Farben zueinander, und ihrer vollständigen Aﬃnität, mit angehängtem Versuch einer Ableitung der Harmonie in den Zusammenstellungen der Farben. Hamburg: Friedrich Perthes. Original artist: Philipp Otto Runge • File:SRGB_gamma.svg Source: https://upload.wikimedia.org/wikipedia/commons/e/ef/SRGB_gamma.svg License: Public domain Con- tributors: Transferred from en.wikipedia to Commons by Shizhao using CommonsHelper. 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• File:SRGB_gamut_within_CIELCHab_color_space_isosurface.png Source: https://upload.wikimedia.org/wikipedia/commons/c/ cf/SRGB_gamut_within_CIELCHab_color_space_isosurface.png License: GFDL Contributors: Own work Original artist: SharkD • File:Saturationdemo.png Source: https://upload.wikimedia.org/wikipedia/commons/f/f0/Saturationdemo.png License: Public domain Contributors: en:File:Saturationdemo.png Original artist: Lefty (2006-03-04), inspired by Coyne Tibbets (CoyneT), 03/18/2005 • File:Självporträtt_av_Anders_Zorn_1896.jpg Source: https://upload.wikimedia.org/wikipedia/commons/b/ba/Sj%C3%A4lvportr% C3%A4tt_av_Anders_Zorn_1896.jpg License: Public domain Contributors: Unknown Original artist: Anders Zorn • File:Sound-icon.svg Source: https://upload.wikimedia.org/wikipedia/commons/4/47/Sound-icon.svg License: LGPL Contributors: Deriva- tive work from Silsor's versio Original artist: Crystal SVG icon set • File:Spyder4Elite_calibrating.JPG Source: https://upload.wikimedia.org/wikipedia/commons/7/7f/Spyder4Elite_calibrating.JPG Li- cense: CC BY-SA 4.0 Contributors: Own work Original artist: Z22 • File:Srgb-in-cielab.png Source: https://upload.wikimedia.org/wikipedia/commons/6/60/Srgb-in-cielab.png License: CC BY-SA 3.0 Contributors: Own work Original artist: Jacobolus • File:Srgbnonlinearity.png Source: https://upload.wikimedia.org/wikipedia/commons/c/c9/Srgbnonlinearity.png License: CC-BY-SA- 3.0 Contributors: English Wikipedia Original artist: Army1987 (talk) and Dicklyon (talk) • File:Stockmansharpe10degCMFadj2000_popconsens.svg Source: https://upload.wikimedia.org/wikipedia/commons/5/52/Stockmansharpe10degCMFadj2000_ popconsens.svg License: CC0 Contributors: ? 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