DOCSLIB.ORG

Colour Appearance Models • Recent Developments

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Colour Appearance Models • Recent Developments C o l o u r a p p e a r a n c e Ming Ronnier Luo Z h e j i a n g U n i v e r s i t y , Hangzhou, China Scope • CIE Colorimetry • Colour appearance models • Recent developments ICC DevCon 2020 Ming Ronnier Luo 2 Scope CIE Colorimetry Colour appearance models Recent developments CIE 015:2018 Colorimetry 4th Edition s10() m10() l10() 2.5 z () 2.0 1.5 x ( ) y ( ) 1.0 Tristimulus values Tristimulus 0.5 CMF 0.0 380 480 580 680 780 2o & 10o Wavelength ( nm ) SPD Spectral r L* D65 & A hab 120 CIELUV 100 CIELAB XYZ 80 b* 60 40 SPD b* 20 a* CIEDE2000 CIE LEDs 0 -60 -40 -20 0 20 40 60 80 100 120 CIECAM02 -20 -40 -60 a* CAM02-UCS C*ab CIE 015:2018 Colorimetry 4th Edition New CIE LED illuminants 0.35 0.6 0.3 0.5 0.25 0.4 0.2 0.3 Target 0.15 Target 0.2 0.1 0.05 0.1 0 0 360nm 410nm 460nm 510nm 560nm 610nm 660nm 710nm 760nm 360nm 410nm 460nm 510nm 560nm 610nm 660nm 710nm 760nm wavelength wavelength LED-B1 LED-B2 LED-B3 LED-B4 LED-B5 LED-BH1 LED-RGB1 LED-V1 LED-V2 Colour Appearance Model Lightness (J) Redness-Greenness (a) Yellowness-Blueness (b) X Y Z CIECAM02 Light Sources (CIECAM16) Chroma (C) Colourfulness (M) Saturation (s) Hue angle (h) X Y Z Ref. w w w LA Yb Surround: Hue composition (H) white Average, Dim and Dark Colour appearance attributes • Lightness • Brightness • Chroma • Colourfulness • Saturation • Hue angle • Hue composition 1. M. R. Luo, et. al. Quantifying colour appearance: Part I CRA 16 (1991) 166-180. 2. M. R. Luo, et. al. Quantifying colour appearance: Part II CRA 16 (1991) 181-197. 3. M. R. Luo, et al., Quantifying colour appearance: Part III CRA 18 (1993) 98-113. 4. M. R. Luo, et al., Quantifying colour appearance: Part IV CRA 18 (1993) 191-209. 5. M. R. Luo, et al., Quantifying colour appearance: Part V CRA 20 (1995) 18-35. Relationship between the absolute and relative colour appearance attributes Brightness Lightness = Brightnesswhite Colourfuln ess Chroma = Brightnesswhite Colourfuln ess Chroma Brightness Saturation = = white Brightness Lightness Brightnesswhite Chroma = Lightness Visual Phenomena 1. Chromatic adaptation effect 2. Hunt effect 3. Stevens effect 4. Surround effect 5. Lightness contrast effect Chromatic Adaptation Green Red Open end - SE Open circle - A Blue Hunt Effect 180 160 C*=80 140 120 C*=60 100 80 C*=40 60 C*=20 40 20 C*=0 0 -2 -1 0 1 2 3 4 5 6 log 10Lw Stevens Effect 800 700 L*=80 600 500 L*=60 400 L*=40 300 L*=20 200 100 L*=0.01 0 -2 -1 0 1 2 3 4 5 6 log10Lw CIE Colour Appearance Models • CIECAM97s • CIE TC1-34 Testing colour appearance models • M. R. Luo and R. W. G. Hunt, The structures of the CIE 1997 colour appearance model (CIECAM97s), Color Res. Appl., 23 138-146 (1998). • CIECAM02 • CIE TC8-01 Colour Appearance Modelling for Colour Management Applications, Scottsdale, Arizona, USA (1998-2002) • N. Moroney, M. D. Fairchild, R.W.G. Hunt, C Li, M. R. Luo and T. Newman, The CIECAM02 Color Appearance Model, CIC2002, Scottsdale, Arizona, pp23-27. • CIECAM16 • CIE JTC10 A new colour appearance model for colour management systems: CIECAM16, （Jiju, South Korea 2017- 2020). • C. J. Li. Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. H. Cui, M. Melgosa, M. H. Brill, and M. R. Pointer, Comprehensive color solutions, CAM16, CAT16 and CAM16-UCS, Col., Res. and Appl., (2017), pp42703-718. Uniform Colour Spaces 120 100 b* b 100 80 80 60 60 40 40 20 20 a 0 a* 0 -20 -20 -40 -40 -60 -60 -60 -40 -20 0 20 40 60 80 100 120 -60 -40 -20 0 20 40 60 80 100 CIELAB CAM02-UCS M. R. Luo, G. Cui, C. Li, Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model, Color Res. Appl. 31 (2006) 320-330. Scope CIE Colorimetry Colour appearance models Recent developments CIECAM Input and output parameters Related Red-Green (a) Lightness (J’) Redness Greenness Yellow-blue (b) Red-Green (a’) X Y Z Brightness (Q) Yellow-blue (b’) Lightness (J) Colourfulness (M’) Achromatic Hue angle (h) signal Colourfulness (M) Chroma (C) DJ’, DM’, DH, DEJ’a’b’ Saturation (s) Yellowness Blueness Hue angle (h) Hue composition (H) Unrelated Brightness (Qun) Colourfulness (Mun) White amount (Wun) Hue Surround: Angle subtense Xw Yw Zw LA Yb Average, Dim (q) and Dark Recent developments Incomplete chromatic adaptation CAT02- Incomplete adaptation Zhai et al, OE 26(2018)7724-39 Zhu et al, CRA(DOI/10.1002/Col.22500) 1 surface 0.8 self-luminous projector Present result 0.6 D 0.4 0.2 0 2500 5000 7500 10000 CCT/K D=F{1-(1/3.6)e[(-La-42)/92] } 2 2 D=a0+a1du’+a2dv’+a3sqrt(du’ +dv’ ) D= Function (Surround, La, [CCT, Duv] or [u’v’], Area, Time, media) Y. Zhu, M. Wei, M. R. Luo, Effects of Adapting Chromaticities and Luminance on Color Appearance on Computer Displays Using Memory, Color Res. and Appl., 000-000 Simultaneous colour contrast 1 ∆H 0.5 0 ∆h -180 -120 -60 0 60 120 180 -0.5 -1 modeling_7° modeling_15° 20 Result (ΔL*) result 15 10 5 0 Background（ΔL*） -100 -50 0 50 100 -5 -10 Y. Zhu and M. R. Luo, (O) Proposed Modification to the CAM16 Colour Appearance Model to Predict the Simultaneous Colour Contrast Effect, 27th Color and Imaging Conference (2019), Paris, 2019, pp190-194. Whiteness-Depth Blackness-Vividness 3 2 r = -0.82 Whiteness 1 0 -1 -2 British Observer Response Observer British -3 0 20 40 60 80 100 Depth (Dab*) Saturation Whiteness 3 2 r = -0.86 1 Blackness 0 -1 -2 Blackness Observer ResponseBritish -3 0 20 40 60 80 100 Vividness (Vab*) Y. J. Cho, L. C. Ou and M. R. Luo, A cross-culture comparison of saturation, vividness, blackness and whiteness scales, Color Res and Appl.,42(2017)203-215 Meaningful colour appearance scales Wang and Luo, R&A, 10(2018)458-470 80 PR650 70 Whiteness – Depth 60 L* 50 Blackness - Vividness 40 Caucasian Oriental 30 South Asian 20 0 10 20 30 40 C*ab Back yard of CII (Derby) Point 1~10 sky Point 11~20 plants Point 21~30 building Jzazbz Model for HDR/WCG M. Safdar, G. Cui, Y. J. kim and M. R. Luo, Perceptually uniform color space for image signals including high dynamic range and wide gamut, Optics Express, 25(2017), pp15131-15151. COMBVF Ellipses CIELAB CAM16-UCS 100 40 30 50 20 10 M b b* 0 0 -10 -20 -50 -30 -40 -50 0 50 100 -40 -20 0 20 40 a a* M IPT J a b z z z 5 0.15 4 0.1 3 2 0.05 z b T 1 0 0 -1 -0.05 -2 -0.1 -3 -0.1 -0.05 0 0.05 0.1 0.15 -2 0 2 4 a P z Hung & Berns Data Hue Linearity - WCG Unitary Hue Data Other Hue Data UCS’s performance Rescaled Chromatic discrimination ellipses in J a b z z z Rescaled Chromatic discrimination ellipses in CAM02-UCS b b z M 0.15 40 30 0.1 2 20 1 푁 퐴푖 σ푖=1 − 1 0.05 푁 퐵푖 10 a a 푳풐풄풂풍 = × 100% (8) z M 1 -0.15 -0.1 -0.05 0.05 0.1 0.15 -0.05 -10 -20 1 2 -0.1 푁 ҧ σ푖=1 푆푖 − 푆 -30 푁 퐺푙표푏푎푙 = × 100% (9) -0.15 ҧ -40 푆 Rescaled Chromatic discrimination ellipses in IC C T P Rescaled Chromatic discrimination ellipses in CIELAB C T b* -0.3 100 Colour Spaces Local (%) Global (%) -0.2 CIELAB 222 48 50 -0.1 CAM02-UCS 138 31 -0.3 -0.2 -0.1 0.1 0.2 0.3 a* ICTCP 175 59 C P -100 -50 50 100 Jzazbz 160 67 0.1 -50 0.2 0.3 -100 CIECAM Input and output parameters 1D-scales 2D-scales Redness Greenness Related X Y Z UCS Vividness (V) Brightness (Q) Depth (D) Achromatic Lightness (J) signal Lightness (J’) Saturation (s) Colourfulness (M) Colourfulness (M’) Blackness (K) Chroma (C) Hue angle (h) Whiteness (W) Yellowness Saturation (s) Blueness DJ’, DM’, DH, DEJ’a’b’ Hue angle (h) Clarity (Cl) Hue composition (H) Y Xw Yw Zw LA b Surround: Angle subtense Average, Dim (q) and Dark Colou reproduction • Spectral (R%) • Relative Colorimetric (XYZ) • Absolute Colorimetric (XL YL ZL) • Appearance (JCh, QMh) • Preference (JCh, QMh) Go beyond colour! CMF CIE 2015 2o & 10o colorimetry SPD Spectral D65 & A reflectance Translucency XYZ CIEDE2000 CIELAB CIELUV CAM16 Total ZCAM Appearance Gloss CAT16 (D) CAM02-UCS 2D colour appearance Jzazbz Unrelated Spatial colour differences Texture colours Colour HDR/WCG contrast Conclusions • Colour appearance models • viewing parameters, Correlates, Visual phenomena • Recent developments • CAT-D • Colour contrast • 2D-colour appearance scales 1 0.8 • Jzazbz UCS 0.6 0.4 • HDR and WCG applications 0.2 0 • Hue linearity 380 480 580 680 Thanks for your attention! Cel.zju.edu.cn [email protected].
Load more

Recommended publications
  • Applying CIECAM02 for Mobile Display Viewing Conditions
    Applying CIECAM02 for Mobile Display Viewing Conditions YungKyung Park*, ChangJun Li*, M. R. Luo*, Youngshin Kwak**, Du-Sik Park **, and Changyeong Kim**; * University of Leeds, Colour Imaging Lab, UK*, ** Samsung Advanced Institute of Technology, Yongin, South Korea** Abstract Small displays are widely used for mobile phones, PDA and 0.7 Portable DVD players. They are small to be carried around and 0.6 viewed under various surround conditions. An experiment was carried out to accumulate colour appearance data on a 2 inch 0.5 mobile phone display, a 4 inch PDA display and a 7 inch LCD 0.4 display using the magnitude estimation method. It was divided into v' 12 experimental phases according to four surround conditions 0.3 (dark, dim, average, and bright). The visual results in terms of 0.2 lightness, colourfulness, brightness and hue from different phases were used to test and refine the CIE colour appearance model, 0.1 CIECAM02 [1]. The refined model is based on continuous 0 functions to calculate different surround parameters for mobile 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 displays. There was a large improvement of the model u' performance, especially for bright surround condition. Figure 1. The colour gamut of the three displays studied. Introduction Many previous colour appearance studies were carried out using household TV or PC displays viewed under rather restricted viewing conditions. In practice, the colour appearance of mobile displays is affected by a variety of viewing conditions. First of all, the display size is much smaller than the other displays as it is built to be carried around easily.
    [Show full text]
  • Computational Color Harmony Based on Coloroid System
    Computational Aesthetics in Graphics, Visualization and Imaging (2005) L. Neumann, M. Sbert, B. Gooch, W. Purgathofer (Editors) Computational Color Harmony based on Coloroid System László Neumanny, Antal Nemcsicsz, and Attila Neumannx yGrup de Gràfics de Girona, Universitat de Girona, and Institució Catalana de Recerca i Estudis Avançats, ICREA, Barcelona, Spain zBudapest University of Technology and Economics, Hungary xInstitute of Computer Graphics and Algorithms, Vienna University of Technology, Austria [email protected], [email protected], [email protected] (a) (b) Figure 1: (a) visualization of the overall appearance of a dichromatic color set with `caleidoscope' option of the Color Plan Designer software and (b) interactive color selection of a dichromatic color set in multi-layer mode, applying rotated regular grid. Abstract This paper presents experimentally based rules and methods for the creation of harmonic color sets. First, dichro- matic rules are presented which concern the harmony relationships of two hues. For an arbitrarily given hue pair, we define the just harmonic saturation values, resulting in minimally harmonic color pairs. These values express the fuzzy border between harmony and disharmony regions using a single scalar. Second, the value of harmony is defined corresponding to the contrast of lightness, i.e. the difference of perceptual lightness values. Third, we formulate the harmony value of the saturation contrast, depending on hue and lightness. The results of these investigations form a basis for a unified, coherent dichromatic harmony formula as well as for analysis of polychromatic color harmony. Introduced color harmony rules are based on Coloroid, which is one of the 5 6 main color-order systems and − furthermore it is an aesthetically uniform continuous color space.
    [Show full text]
  • A Guide to Colorimetry
    A Guide to Colorimetry Sherwood Scientific Ltd 1 The Paddocks Cherry Hinton Road Cambridge CB1 8DH England www.sherwood-scientific.com Tel: +44 (0)1223 243444 Fax: +44 (0)1223 243300 Registered in England and Wales Registration Number 2329039 Reg. Office as above Group I II III IV V VI VII VIII Period 1A 8A 1 2 1 H 2A 3A 4A 5A 6A 7A He 1.008 4.003 3 4 5 6 7 8 9 10 2 Li Be B C N O F Ne 6.939 9.0122 10.811 12.011 14.007 15.999 18.998 20.183 11 12 13 14 15 16 17 18 3 Na Mg 3B 4B 5B 6B 7B [---------------8B-------------] 1B 2B Al Si P S Cl Ar 22.99 24.312 26.982 28.086 30.974 32.064 35.453 39.948 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 4 K Ca Sc Ti V Cr Mn Fe Co Ni Cu Zn Ga Ge As Se Br Kr 39.102 40.08 44.956 47.9 50.942 51.996 54.938 55.847 58.933 58.71 63.546 65.37 69.72 72.59 74.922 78.96 79.904 83.8 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 5 Rb Sr Y Zr Nb Mo Tc Ru Rh Pd Ag Cd In Sn Sb Te I Xe 85.47 87.52 88.905 91.22 92.906 95.94 [97] 101.07 102.91 106.4 107.87 112.4 114.82 118.69 121.75 127.6 126.9 131.3 55 56 57* 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 6 Cs Ba La Hf Ta W Re Os Ir Pt Au Hg Ti Pb Bi Po At Rn 132.91 137.34 138.91 178.49 180.95 183.85 186.2 190.2 192.2 195.09 196.97 200.59 204.37 207.19 208.98 209 210 222 87 88 89** 104 105 106 107 108 109 110 111 112 114 116 7 Fr Ra Ac Rt Db Sg Bh Hs Mt 215 226.03 227.03 [261] [262] [266] [264] [269] [268] [271] [272] [277] [289] [289] 58 59 60 61 62 63 64 65 66 67 68 69 70 71 * Lanthanides Ce Pr Nd Pm Sm Eu Gd Tb Dy Ho Er Tm Yb Lu 140.12 140.91 144.24 145 150.35 151.96 157.25 158.92 152.5 164.93 167.26 168.93 173.04 174.97 90 91 92 93 94 95 96 97 98 99 100 101 102 103 ** Actinides Th Pa U Np Pu Am Cm Bk Cf Es Fm Md No Lr 232.04 231 238 237.05 239.05 241.06 244.06 249.08 251 252.08 257.1 258.1 259.1 262.11 The ability to analyse and quantify colour in aqueous solutions and liquids using a colorimeter is something today’s analyst takes for granted.
    [Show full text]
  • Illumination and Distance
    PHYS 1400: Physical Science Laboratory Manual ILLUMINATION AND DISTANCE INTRODUCTION How bright is that light? You know, from experience, that a 100W light bulb is brighter than a 60W bulb. The wattage measures the energy used by the bulb, which depends on the bulb, not on where the person observing it is located. But you also know that how bright the light looks does depend on how far away it is. That 100W bulb is still emitting the same amount of energy every second, but if you are farther away from it, the energy is spread out over a greater area. You receive less energy, and perceive the light as less bright. But because the light energy is spread out over an area, it’s not a linear relationship. When you double the distance, the energy is spread out over four times as much area. If you triple the distance, the area is nine Twice the distance, ¼ as bright. Triple the distance? 11% as bright. times as great, meaning that you receive only 1/9 (or 11%) as much energy from the light source. To quantify the amount of light, we will use units called lux. The idea is simple: energy emitted per second (Watts), spread out over an area (square meters). However, a lux is not a W/m2! A lux is a lumen per m2. So, what is a lumen? Technically, it’s one candela emitted uniformly across a solid angle of 1 steradian. That’s not helping, is it? Examine the figure above. The source emits light (energy) in all directions simultaneously.
    [Show full text]
  • Color Space Conversion
    L Technical Color Space Information Conversion The role of color space conversion in the process of scanning and reproduc- ing a color image begins the moment an image is captured by a scanner and continues through the point at which it is output on film. For the purpose of this article we will discuss conversions between three types of color systems: RGB, CIE, and CMYK. The RGB (Red, Green, & Blue) and CMYK (Cyan, Magenta, Yellow, & Black) color models have been described in greater detail in the Linotype-Hell Technical information piece entitled Color in Printing. For some background information on the CIE (Commission Internationale de l’Eclairage), please refer to Color Spaces and PostScript Level 2. CIE as a reference color space Most scanners acquire color in the form of RGB data. The majority of non- photographic printing methods employ CMYK inks or toners. In a closed sys- tem, where the characteristics of both the scanner and the printing method are well-defined, conversions may be made from RGB to CMYK through tables that maintain a reasonable level of color consistency. The process becomes somewhat more difficult as you add monitors, other scanners, proofing devices or printing processes that have different characteristics. It becomes critical to have a consistent yardstick, if you will, a means of con- verting between different color systems (and back again) without a loss in color fidelity. This is what CIE provides. Let’s start with some background on CIE, and then we will look at how it can be applied in an open system. Measuring color Light reflected off of, or transmitted through a colored object can be mea- sured by the wavelengths of light that are reflected or transmitted.
    [Show full text]
  • Package 'Colorspace'
    Package ‘colorspace’ February 15, 2013 Version 1.2-1 Date 2013-01-24 Title Color Space Manipulation Description Carries out mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV),CIELAB and po- lar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided. Depends R (>= 2.10.0), methods Suggests KernSmooth, MASS, kernlab, mvtnorm, vcd, tcltk, dichromat License BSD LazyData yes Author Ross Ihaka [aut], Paul Murrell [aut], Kurt Hornik [aut], Jason C. Fisher [aut], Achim Zeileis [aut, cre] Maintainer Achim Zeileis <[email protected]> Repository CRAN Date/Publication 2013-01-24 14:59:08 NeedsCompilation yes R topics documented: choose_palette . .2 color-class . .3 coords . .4 desaturate . .5 hex..............................................6 hex2RGB . .7 HLS.............................................8 1 2 choose_palette HSV.............................................9 LAB............................................. 10 LUV............................................. 11 mixcolor . 12 polarLAB . 13 polarLUV . 14 rainbow_hcl . 15 readhex . 18 readRGB . 19 RGB............................................. 20 sRGB ............................................ 21 USSouthPolygon . 22 writehex . 22 XYZ............................................. 23 Index 25 choose_palette Graphical User Interface for Choosing HCL Color Palettes Description A graphical user interface (GUI) for viewing, manipulating, and choosing HCL color palettes. Usage choose_palette(pal
    [Show full text]
  • 1 Human Color Vision
    CAMC01 9/30/04 3:13 PM Page 1 1 Human Color Vision Color appearance models aim to extend basic colorimetry to the level of speci- fying the perceived color of stimuli in a wide variety of viewing conditions. To fully appreciate the formulation, implementation, and application of color appearance models, several fundamental topics in color science must first be understood. These are the topics of the first few chapters of this book. Since color appearance represents several of the dimensions of our visual experience, any system designed to predict correlates to these experiences must be based, to some degree, on the form and function of the human visual system. All of the color appearance models described in this book are derived with human visual function in mind. It becomes much simpler to understand the formulations of the various models if the basic anatomy, physiology, and performance of the visual system is understood. Thus, this book begins with a treatment of the human visual system. As necessitated by the limited scope available in a single chapter, this treatment of the visual system is an overview of the topics most important for an appreciation of color appearance modeling. The field of vision science is immense and fascinating. Readers are encouraged to explore the liter- ature and the many useful texts on human vision in order to gain further insight and details. Of particular note are the review paper on the mechan- isms of color vision by Lennie and D’Zmura (1988), the text on human color vision by Kaiser and Boynton (1996), the more general text on the founda- tions of vision by Wandell (1995), the comprehensive treatment by Palmer (1999), and edited collections on color vision by Backhaus et al.
    [Show full text]
  • Sunlight Readability and Luminance Characteristics of Light
    SUNLIGHT READABILITY AND LUMINANCE CHARACTERISTICS OF LIGHT- EMITTING DIODE PUSH BUTTON SWITCHES Robert J. Fitch, B.S.E.E., M.B.A. Thesis Prepared for the Degree of MASTER OF SCIENCE UNIVERSITY OF NORTH TEXAS May 2004 APPROVED: Albert B. Grubbs, Jr., Major Professor and Chair of the Department of Engineering Technology Don W. Guthrie, Committee Member Michael R. Kozak, Committee Member Roman Stemprok, Committee Member Vijay Vaidyanathan, Committee Member Oscar N. Garcia, Dean of the College of Engineering Sandra L. Terrell, Interim Dean of the Robert B. Toulouse School of Graduate Studies Fitch, Robert J., Sunlight readability and luminance characteristics of light- emitting diode push button switches. Master of Science (Engineering Technology), May 2004, 69 pp., 7 tables, 9 illustrations, references, 22 titles. Lighted push button switches and indicators serve many purposes in cockpits, shipboard applications and military ground vehicles. The quality of lighting produced by switches is vital to operators’ understanding of the information displayed. Utilizing LED technology in lighted switches has challenges that can adversely affect lighting quality. Incomplete data exists to educate consumers about potential differences in LED switch performance between different manufacturers. LED switches from four different manufacturers were tested for six attributes of lighting quality: average luminance and power consumption at full voltage, sunlight readable contrast, luminance contrast under ambient sunlight, legend uniformity, and dual-color uniformity. Three of the four manufacturers have not developed LED push button switches that meet lighting quality standards established with incandescent technology. Copyright 2004 by Robert J. Fitch ii ACKNOWLEDGMENTS I thank Don Guthrie and John Dillow at Aerospace Optics, Fort Worth, Texas, for providing the test samples, lending the use of their laboratories, and providing tremendous support for this research.
    [Show full text]
  • The Helmholtz-Kohlrausch Effect
    Out of the Wood BY MIKE WOOD Lightness— The Helmholtz-Kohlrausch effect Don’t be put off by the strange name also strongly suggest looking at the online lightness most people see when looking at of this issue’s article. The Helmholtz- version of this article, as the images will be this image. Kohlrausch (HK) effect might sound displayed on your monitor and behave Note: Not everyone will see the differences esoteric, but it’s a human eye behavioral more like lights than the ink pigments in as strongly, particularly with a printed page effect with colored lighting that you are the printed copy. You can access Protocol like this. Just about everyone sees this effect undoubtedly already familiar with, if issues on-line at http://plasa.me/protocol with lights, but the strength of the effect varies perhaps not under its formal name. This or through the iPhone or iPad App at from individual to individual. In particular, effect refers to the human eye (or entoptic) http://plasa.me/protocolapp. if you are red-green color-blind, then you may phenomenon that colored light appears The simplest way to show the Helmholtz- see very little difference. brighter to us than white light of the same Kohlrausch effect is with an illustration. What I see—which will agree with what luminance. This is particularly relevant to The top half of Figure 1 shows seven most of you see—is that the red and pink the entertainment industry, as it is most differently colored patches against a grey patches look by far the brightest, while blue, obvious when using colored lights.
    [Show full text]
  • RAL-Product-2019-SC-1.Pdf
    INHALT / PRODUKTÜBERSICHT / RAL FARBEN PRODUCT OVERVIEW RAL COLOURS – Innovation and reliability. Worldwide. RAL FARBEN / PRODUKTÜBERSICHT / INHALT RAL CLASSIC THE WORLD‘S LEADING INDUSTRIAL COLOUR COLLECTION The RAL CLASSIC colour collection has for 90 years been indispensable in the clear communication of colours and a guarantee for obtaining exactly the same colours – worldwide. APPLICATION EXAMPLES Steel sculpture by world famous sculptor Anish Kapoor and star architect Cecil Balmond is London’s Olympic landmark. The ArcelorMittal Orbit glows in RAL 3003 Ruby Red. Allmilmö – a leading premium brand manufacturer of high-quality kitchen furnishings – produces these kitchen models in RAL 1023 traffic yellow. A design classic that is available in various colours. The picture shows a model in RAL 1004 Golden yellow. Emergency exit signs have the colour RAL 6002 Leaf green. Thonet produces the S 43 cantilever chair by Mart Stam in 11 RAL colours. RAL CLASSIC / PRODUCT OVERVIEW / RAL COLOURS RAL 840-HR Primary standards with 213 RAL CLASSIC colours Semi matt A5-sized 14.8 x 21.0 cm Colour illustration A6-sized 10.5 x 14.8 cm Binding colour samples for colour matching and quality control RAL 840-HR | 841-GL Including XYZ-values, colour distance from the original standard and reflectance curve Single cards available RAL 841-GL Primary standards with 196 RAL CLASSIC colours High gloss Allmilmö – a leading premium brand manufacturer of high-quality kitchen furnishings – A5-sized 14.8 x 21.0 cm produces these kitchen models in RAL 1023 traffic yellow. Colour illustration A6-sized 10.5 x 14.8 cm Binding colour samples for colour matching and quality control Including XYZ-values, colour distance from the original standard and reflectance curve Single cards available 07 Thonet produces the S 43 cantilever chair by Mart Stam in 11 RAL colours.
    [Show full text]
  • Color Appearance Models Today's Topic
    Color Appearance Models Arjun Satish Mitsunobu Sugimoto 1 Today's topic Color Appearance Models CIELAB The Nayatani et al. Model The Hunt Model The RLAB Model 2 1 Terminology recap Color Hue Brightness/Lightness Colorfulness/Chroma Saturation 3 Color Attribute of visual perception consisting of any combination of chromatic and achromatic content. Chromatic name Achromatic name others 4 2 Hue Attribute of a visual sensation according to which an area appears to be similar to one of the perceived colors Often refers red, green, blue, and yellow 5 Brightness Attribute of a visual sensation according to which an area appears to emit more or less light. Absolute level of the perception 6 3 Lightness The brightness of an area judged as a ratio to the brightness of a similarly illuminated area that appears to be white Relative amount of light reflected, or relative brightness normalized for changes in the illumination and view conditions 7 Colorfulness Attribute of a visual sensation according to which the perceived color of an area appears to be more or less chromatic 8 4 Chroma Colorfulness of an area judged as a ratio of the brightness of a similarly illuminated area that appears white Relationship between colorfulness and chroma is similar to relationship between brightness and lightness 9 Saturation Colorfulness of an area judged as a ratio to its brightness Chroma – ratio to white Saturation – ratio to its brightness 10 5 Definition of Color Appearance Model so much description of color such as: wavelength, cone response, tristimulus values, chromaticity coordinates, color spaces, … it is difficult to distinguish them correctly We need a model which makes them straightforward 11 Definition of Color Appearance Model CIE Technical Committee 1-34 (TC1-34) (Comission Internationale de l'Eclairage) They agreed on the following definition: A color appearance model is any model that includes predictors of at least the relative color-appearance attributes of lightness, chroma, and hue.
    [Show full text]
  • Chromatic Adaptation Transform by Spectral Reconstruction Scott A
    Chromatic Adaptation Transform by Spectral Reconstruction Scott A. Burns, University of Illinois at Urbana-Champaign, [email protected] February 28, 2019 Note to readers: This version of the paper is a preprint of a paper to appear in Color Research and Application in October 2019 (Citation: Burns SA. Chromatic adaptation transform by spectral reconstruction. Color Res Appl. 2019;44(5):682-693). The full text of the final version is available courtesy of Wiley Content Sharing initiative at: https://rdcu.be/bEZbD. The final published version differs substantially from the preprint shown here, as follows. The claims of negative tristimulus values being “failures” of a CAT are removed, since in some circumstances such as with “supersaturated” colors, it may be reasonable for a CAT to produce such results. The revised version simply states that in certain applications, tristimulus values outside the spectral locus or having negative values are undesirable. In these cases, the proposed method will guarantee that the destination colors will always be within the spectral locus. Abstract: A color appearance model (CAM) is an advanced colorimetric tool used to predict color appearance under a wide variety of viewing conditions. A chromatic adaptation transform (CAT) is an integral part of a CAM. Its role is to predict “corresponding colors,” that is, a pair of colors that have the same color appearance when viewed under different illuminants, after partial or full adaptation to each illuminant. Modern CATs perform well when applied to a limited range of illuminant pairs and a limited range of source (test) colors. However, they can fail if operated outside these ranges.
    [Show full text]