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- Gamma X rays violet Infrared Radar FM TV wave AM AC electricity 10-12 10-8 10-4 10 4 1 10 8 Visible light Wavelength in meters (m) 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 Relative Power 1 0.5 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 ganglion horizontal amacrine 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 G B Brightness Hue black-white blue-yellow 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.) Primary Intensity 3 2 1 0 400 500 600 Wavelength (nm) 700 23
Color Matching Experiment test match + - + - + - Three primary lights are set to match a test light 1 Test light 1 Match light 0.75 0.5 0.25 = ~ 0.75 0.5 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 200 14 36 36 12 36 200 111 14 14 361261217 36111 14 36 10 1283612636200 17111 12 11136 111 14 14 12636 17 111 17 36 1736 126 1412 7236 126 126 72 200 17 36111 12 36 12 14 17 200 1263617 12111 3620012 2007236 12 12 171261117 14 126 36 126 200 111 14 36 72 36 12 17 72 106 155 10 128 126 200 12 111 200 36 12 36 14 36 111 14 126 36 12 36 17 36 36 14 36 72 200 111 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 36 12 17 72 12 17 72 111 106 14 155 36 12 126 200 36 12 36 26
RGB Color Model Colors are additive 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? Plate II.3 from FvDFH
RGB Color Cube Figures 15.11&15.12 from H&B
CMYK Color Model transmit Cyan removes Red B G R Magenta removes Green CMYK = Cyan, Magenta, Yellow, black B G R Yellow removes Blue B G R Black removes all 29
Combining Colors Additive (RGB) Subtractive (CMYK) 30
magenta Example: red = magenta + yellow B G R + B G R yellow = red B G R B G R 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
38 From RGB to CMY = B G R Y M C 1 1 1 = Y M C B G R 1 1 1
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) Value: 0... 10 (dark... pure white) Chroma: 0... 20 (neutral... saturated) Example: 5YR 8/4 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 Saturation Value Hue 44
HLS Color Space HLS = Hue Lightness Saturation V green 120 yellow cyan 0.5 red 0 Blue 240 magenta 0.0 black H S 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: r R G =, g = R+ G+ B R+ G+ B 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 Non negative over the visible wavelengths. The 3 primaries associated with x y z spectral power distribution are unrealizable (negative power in some of the wavelengths). The color matching of Y is equal to the spectral luminous efficiency curve. Tristimulus values 1.8 1.4 1 0.6 0.2 XYZ Color Matching Functions z(λ) y(λ) x(λ) 400 500 600 700 Wavelength (nm) 53
RGB to XYZ RGB to XYZ is a linear transformation X Y Z = 0.490 0.310 0.200 0.177 0.813 0.011 0.000 0.010 0.990 R G B 54
CIE Chromaticity Diagram 0.9 520 530 X X = x X+Y+Z y 510 505 500 0.5 495 490 540 550 560 570 580 590 600 610 650 Y Z Y = y X+Y+Z Z = z X+Y+Z x+y+z = 1 485 480 0.0 0.0 470 450 0.5 x 1.0 55
Color Naming y 0.9 510 505 0.5 500 495 490 520 530 green cyan 540 550 560 yellowgreen white pink 570 580 yellow orange 590 600 610 650 red 0.0 485 480 blue purple 470 450 magenta x 0.5 1.0 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. Dominant Wavelength wavelength of the spectral color which added to the reference white, produces the given color. 0.8 0.6 0.4 0.2 reference white 0 0 0.2 0.4 0.6 0.8 59
Chromaticity Defined in Polar Coordinates Given a reference white. Dominant Wavelength Complementary Wavelength - wavelength of the spectral color which added to the given color, produces the reference white. 0.8 0.6 0.4 0.2 reference white 0 0 0.2 0.4 0.6 0.8 60
Chromaticity Defined in Polar Coordinates Given a reference white. Dominant Wavelength Complementary Wavelength Excitation Purity the ratio of the lengths between the given color and reference white and between the dominant wavelength light and reference white. Ranges between 0.. 1. 0.8 0.6 0.4 0.2 0 purity reference white 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: Equal brightness steps: Luminance I1 I1 I2 I2 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 I = constant (I is intensity, I is change in intensity) Weber s Law: Perceived Brightness = log (I) Perceived Brightness Intensity 66
Munsell lines of constant Hue and Chroma 0.5 0.4 y 0.3 0.2 0.1 0 0 0.1 0.2 0.3 0.4 0.5 0.6 x Value =1/ 67
MacAdam Ellipses of JND (Just Noticeable Difference) 0.8 y 0.6 0.4 (Ellipses 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 50 Value =5/ 100 50 0 v * -50-100 0 v * -50-100 -150-150 -100-50 0 u * 50 100 150 200-150 -150-100 -50 0 50 100 150 200 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
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