COLOR and the human response to light Contents

 Introduction:

 The nature of light

 The physiology of human vision  Color Spaces:

 Linear

 Artistic View  Standard  Distances between colors  Color in the TV

2 Amazing

3 Introduction

4 Electromagnetic Radiation - Spectrum

Ultra- Short- AC Gamma X rays violet Infrared Radar FM TV wave AM electricity

-12 -8 -4 4 8 10 10 10 1 10 10 Wavelength in meters (m) Visible light

400 nm 500 nm 600 nm 700 nm Wavelength in nanometers (nm)

5 Spectral Power Distribution

 The Spectral Power Distribution (SPD) of a light is a function P(λ) which defines the power in the light at each wavelength

1

0.5 Relative Power Relative 0 400 500 600 700 Wavelength (λ)

6 Spectral Power Distribution

White Light Orange Light Figures 15.3-4 from H&B Examples

8 The Interaction of Light and Matter

 Some or all of the light may be absorbed depending on the pigmentation of the object.

9 Interlude: Color is Complicated

What colors make up the spirals? 10 The Physiology of Human Vision

11 The Human Eye

12 The Human Retina

rods cones

bipolar horizontal amacrine ganglion

light 13 The Human Retina

14 Retinal Photoreceptors

15 Cones

 High illumination levels (Photopic vision)

 Less sensitive than rods.

 5 million cones in each eye.

 Density decreases with distance from fovea.

16 3 Types of Cones

 L-cones, most sensitive to red light (610 nm)

 M-cones, most sensitive to green light (560 nm)

 S-cones, most sensitive to blue light (430 nm)

17 Cones Spectral Sensitivity (L, M , S) ⇐ L = ∫ P(λ)L(λ)dλ λ

18 Metamers

 Two lights that appear the same visually. They might have different SPDs (spectral power distributions)

19 History

 Tomas Young (1773-1829) “A few different retinal receptors operating with different wavelength sensitivities will allow humans to perceive the number of colors that they do. “  James Clerk Maxwell (1872) “We are capable of feeling three different color sensations. Light of different kinds excites three sensations in different proportions, and it is by the different combinations of these three primary sensations that all the varieties of visible color are produced. “  Trichromatic: “Tri”=three “chroma”=color

20 3D Color Spaces

 Three types of cones suggests color is a 3D quantity. How to define 3D color space?

Cubic Color Spaces Polar Color Spaces Opponent Color Spaces

Brightness black-white Hue G blue-yellow B

R red-green

21 Linear Color Spaces

Colors in 3D color space can be described as linear combinations of 3 basis colors, called primaries

= a• + b• + c•

The representation of :

is then given by: (a, b, c)

22 RGB Color Model

 RGB = Red, Green, Blue

 Choose 3 primaries as the basis SPDs (Spectral Power Distribution.)

3

2

1 PrimaryIntensity 0 400 500 600 700 Wavelength (nm)

23 Color Matching Experiment

test match + - + - + -

 Three primary lights are set to match a test light

Test light Match light 1 1

0.75 0.75 0.5 ~ 0.5 0.25 = 0.25

0 400 500 600 700 0 400 500 600 700 24 CIE-RGB

 Stiles & Burch (1959) Color matching Experiment.

 Primaries are: 444.4 525.3 645.2

 Given the 3 primaries, we can describe any light with 3 values (CIE-RGB):

(85, 38, 10) (21, 45, 72) (65, 54, 73)

25 RGB Image

111 14 126 36 12 36 36 111 36 12 17 111 200 36 1712 11136 20014 3636 12 36 200 111 1414 36126 1217 36 111 14 36 10 128 36126 36200 17 111 12 111 36 111 14 14 12636 17 111 17 36 1736 12614 12 72 36 126 126 72 200 17 36111 12 36 12 17 200126 3617 12111 36200 12 126 14 200 7236 1212 17126 11117 14 36 10 128 126 200 12 111 126 200 111 14 36 72 200 36 12 36 14 36 111 14 126 36 12 36 17 36 36 14 36 72 36 12 17 72 106 155 200 111 14 126 17 111 36 111 36 12 17 111 12 17 126 17 111 200 36 36 111 36 14 36 17 111 200 36 12 36 14 200 36 12 126 17 17 126 72 126 17 111 14 36 12 36 14 36 126 200 111 14 36 72 200 36 12 36 12 126 17 111 14 126 17 111 17 36 72 12 12 17 72 111 106 14 155 36 12 126 200 36 12 36 26 RGB Color Model R G B Color 0.0 0.0 0.0 Black 1.0 0.0 0.0 Red 0.0 1.0 0.0 Green 0.0 0.0 1.0 Blue 1.0 1.0 0.0 Yellow 1.0 0.0 1.0 Magenta 0.0 1.0 1.0 Cyan 1.0 1.0 1.0 White 0.5 0.0 0.0 ? 1.0 0.5 0.5 ? 1.0 0.5 0.0 ? 0.5 0.3 0.1 ? Colors are additive Plate II.3 from FvDFH RGB Color Cube

Figures 15.11&15.12 from H&B CMYK Color Model

CMYK = Cyan, Magenta, Yellow, blacK Cyan – removes Red transmit B G R Magenta – removes Green

B G R Yellow – removes Blue

B G R Black – removes all 29 Combining Colors

Additive (RGB) Subtractive (CMYK)

30 Example: red = magenta + yellow

B G R

magenta

+ B G R yellow

B G R = red R B G R 31 CMY + Black

C + M + Y = K (black)

 Using three inks for black is expensive

 C+M+Y = dark brown not black

 Black instead of C+M+Y is crisper with more contrast

= + 100 50 70 50 50 0 20 C M Y K C M Y

32 Example

33 Example

34 Example

35 Example

36 Example

37 From RGB to CMY

 C  1  R   R  1  C               M  = 1 − G G = 1 −  M               Y  1  B   B  1  Y 

38 The Artist Point of View

 Hue - The color we see (red, green, purple)

 Saturation - How far is the color from gray (pink is less saturated than red, sky blue is less saturated than royal blue)

 Brightness/Lightness (Luminance) - How bright is the color

white

39 Munsell Color System Equal perceptual steps in Hue Saturation Value. Hue: R, YR, Y, GY, G, BG, B, PB, P, RP (each subdivided into 10) Example: Value: 0 ... 10 (dark ... pure white) 5YR 8/4 Chroma: 0 ... 20 (neutral ... saturated)

40 Munsell Book of Colors

41 Munsell Book of Colors

42 HSV/HSB Color Space

HSV = Hue Saturation Value HSB = Hue Saturation Brightness

Saturation Scale

Brightness Scale

43 HSV

Value Saturation

Hue

44 HLS Color Space

HLS = Hue Lightness Saturation V

green 120° yellow

cyan 0.5 red 0°

Blue 240° magenta

H 0.0 S black

45 Back to RGB

 Problem 1: RGB differ from one device to another

46 CIE 1931 Color Space

 Experiments produced three functions: r(λ), g(λ), b(λ)  Functions were normalized to have a constant area beneath them

 Therefore, RGB tristimulus values for a color I(λ) would be:

47 CIE 1931 Color space

 We can parameterize chromaticity by defining:

RG rg= , = RGB++ RGB ++

48 CIE-XYZ

 Transforming the triangle to (0,0),(0,1),(1,0) is a linear transformation

49 XYZ Color Model (CIE)

Amounts of CIE primaries needed to display spectral colors

CIE primaries are imaginary

Figure 15.6 from H&B Back to RGB

 Problem 2: RGB cannot represent all colors

RGB Color Matching Functions

51 CIE Color Standard - 1931

 CIE - Commision Internationale d’Eclairage  1931 - defined a standard system for color representation.

 XYZ tristimulus coordinate system.

X Y Z

52 XYZ Spectral Power Distribution

XYZ Color Matching Functions  Non negative over the 1.8

visible wavelengths. z(λ)  The 3 primaries associated 1.4 with x y z spectral power y(λ) distribution are unrealizable 1 (negative power in some of x(λ) the wavelengths). 0.6

 The color matching of Y is values Tristimulus equal to the spectral 0.2 luminous efficiency curve. 400 500 600 700 Wavelength (nm)

53 RGB to XYZ

 RGB to XYZ is a linear transformation

X 0.490 0.310 0.200 R = Y 0.177 0.813 0.011 G Z 0.000 0.010 0.990 B

54 CIE Chromaticity Diagram

0.9 X 520 X = x 530 X+Y+Z 510 540 Y 550 Y = y y 505 560 X+Y+Z 570 Z 500 Z = z 0.5 580 X+Y+Z 495 590 600 610 x+y+z = 1 490 650 485 480 470 0.0 450 0.0 0.5 1.0x 55 Color Naming

0.9 520 530 510 540 550 y 505 green 560 570 500 yellow- 0.5 green 580 yellow 495 590 orange 600 white 610 490 cyan pink red 650 485 magenta blue 480 purple 470 450 0.0 0.5 1.0 x 56 Blackbody Radiators and CIE Standard Illuminants

CIE Standard Illuminants:

2500 - tungsten light (A) 4800 - Sunset 10K - blue sky 6500 - Average daylight (D65)

57 RGB Color Gamut for typical monitor

Figure 15.13 from H&B Chromaticity Defined in Polar Coordinates

Given a reference white. 0.8 Dominant Wavelength – wavelength of the spectral color which added to the 0.6 reference white, produces the given color. 0.4

reference white 0.2

0 0 0.2 0.4 0.6 0.8 59 Chromaticity Defined in Polar Coordinates

Given a reference white. 0.8 Dominant Wavelength

Complementary 0.6 Wavelength - wavelength of the spectral color which added to the given color, 0.4 produces the reference reference white white. 0.2

0 0 0.2 0.4 0.6 0.8 60 Chromaticity Defined in Polar Coordinates

Given a reference white. 0.8 Dominant Wavelength

Complementary 0.6 Wavelength

purity Excitation Purity – 0.4 the ratio of the lengths reference white between the given color and reference white and 0.2 between the dominant wavelength light and reference white. 0 Ranges between 0 .. 1. 0 0.2 0.4 0.6 0.8 61 Device Color Gamut

 We can use the CIE chromaticity diagram to compare the gamut of various devices:

 Note, for example, that a color printer cannot reproduce all shades available on a color monitor

62 But wait there’s more

 We still haven’t talked about

 Color appearance model

 Dynamic range (low and high)

Starry night / Van Gogh 63

Luminance v.s. Brightness

Luminance Brightness (intensity) vs (Lightness) Y in XYZ V in HSV

Equal intensity steps:

∆I2 I2 Equal brightness steps: ∆I1 Luminance I1

I1 < I2, ∆I1 = ∆I2

65 Weber’s Law

In general, ∆I needed for just noticeable difference (JND) over background I was found to satisfy:

∆I = constant I

(I is intensity, ∆I is change in intensity) Weber’s Law: Perceived Brightness Perceived Brightness = log (I) Intensity

66 Munsell lines of constant Hue and Chroma

0.5

0.4

0.3 y

0.2

0.1 Value =1/ 0 0 0.1 0.2 0.3 0.4 0.5 0.6 x

67 MacAdam Ellipses of JND (Just Noticeable Difference)

0.8

0.6 y (Ellipses 0.4 scaled by 10)

0.2

0 0 0.2 0.4 0.6 x 68 Perceptual Color Spaces

 An improvement over CIE-XYZ that represents better uniform color spaces

 The transformation from XYZ space to perceptual space is Non Linear.

 Two standard adopted by CIE are L*u’v’ and L*a*b*  The L* line in both spaces is a replacement of the Y lightness scale in the XYZ model, but it is more indicative of the actual visual differences.

69 Munsell Lines and MacAdam Ellipses plotted in CIE-L*u’v’ coordinates

100 Value =5/ 100

50 50

0 * 0 v* v

-50 -50

-100 -100 -150 -150 -150 -100 -50 0 50 100 150 200 -150 -100 -50 0 50 100 150 200 u* u*

70 Distances between colors

 Distances are not linear in any color space.

 In perceptual color space distances are more suitable for our conception.

 Measuring color differences between pixels is more useful in perceptual color spaces.

71 Opponent Color Spaces

+ black-white + blue-yellow

- + red-green

-

-

72 YIQ Color Model

 YIQ is the color model used for color TV in America (NTSC= National Television Systems Committee)  Y is luminance, I & Q are color (I=red/green,Q=blue/yellow)  Note: Y is the same as CIE’s Y  Result: backwards compatibility with B/W TV!  Convert from RGB to YIQ: Y  0.30 0.59 0.11 R       I  = 0.60 − 0.28 − 0.32G Q 0.21 − 0.52 0.31 B  The YIQ model exploits properties of our visual system, which allows to assign different bandwidth for each of the primaries (4 MHz to Y, 1.5 to I and 0.6 to Q) 73

YUV Color Model

 YUV is the color model used for color TV in Israel (PAL), and in video. Also called YCbCr.

 Y is luminance as in YIQ.

 U and V are blue and red (Cb and Cr).

 The YUV uses the same benefits as YIQ, (5.5 MHz for Y, 1.3 for U and V).

 Converting from RGB to YUV:

 Y = 0.299R + 0.587G + 0.114B

 U = 0.492(B – Y)  V = 0.877(R – Y) 74 YUV - Example

Y U V 75 Summary

 Light  Eye (Cones,Rods)  [l,m,s]  Color

 Color standards (Munsell, CIE)

 Many 3D color models:

 RGB, CMY, Munsell(HSV/HLS), XYZ, Perceptual(Luv,Lab), Opponent(YIQ,YUV).

 Reproducing Metamers to Colors

 Different reproduction Gamut

 Non-linear distances between colors

76 77