1. Chapter 12 Color Models and Color Applications
Computer Graphics
Chapter 12
Color Models and Color Applications

2. Outline Properties of Light Color Models
Standard Primaries and the Chromaticity Diagram
The RGB Color Model
The YIQ and Related Color Models
The CMY and CMYK Color Models
The HSV Color Model
The HLS Color Model
Color Selection and Applications

3. Properties of Light What is light? The Electromagnetic Spectrum
“light” = narrow frequency band of electromagnetic spectrum
The Electromagnetic Spectrum
Red: 3.8x1014 hertz
Violet: 7.9x1014 hertz

4. Spectrum of Light
Monochrome light can be described by frequency f and wavelength λ
c = λ f (c = speed of light)
Normally, a ray of light contains many different waves with individual frequencies
The associated distribution of wavelength intensities per wavelength is referred to as the spectrum of a given ray or light source

5. The Human Eye

6. Psychological Characteristics of Color
Dominant frequency (hue, color)
Brightness (area under the curve), total light energy
Purity (saturation), how close a light appear to be a pure spectral color, such as red
Purity = ED − EW
ED = dominant energy density
EW = white light energy density
Chromaticity, used to refer collectively to the two properties describing color characteristics: purity and dominant frequency

7. Intuitive Color Concepts
Color mixing created by an artist
Shades, tints and tones in scene can be produced by mixing color pigments (hues) with white and black pigments
Shades
Add black pigment to pure color
The more black pigment, the darker the shade
Tints
Add white pigment to the original color
Making it lighter as more white is added
Tones
Produced by adding both black and white pigments

8. Colorimetry (CM)
CM is the branch of color science concerned with numerically specifying the color of a physically defined visual stimulus
Stimuli with the same specification look alike under the same viewing conditions
Stimuli that look alike have the same specification
The numbers used are continuous functions of the physical parameters
Colorimetry n. measuring of the intensity of color

9. CM Properties
CM only considers the visual discriminability of physical beams of radiation
Colors are an equivalence class of mutually indiscriminable beams
Colors in this sense cannot be said to be “red”, “green” or any other “color name”
Discriminability is decided before the brain comes into action - CM is not psychology

10. Color Matching Experiments
Observers had to match a test light by combining three fixed primaries
Goal: find the unique RGB coordinates for each stimulus

11. Tristimulus Values
The values RQ, GQ and BQ for a stimulus Q that fulfill
Q = RQ*R + GQ*G + BQ*B
are called the tristimulus values of Q
R = nm
G = nm
B = nm

12. Negative Light in a CME
if a match using only positive RGB values proved impossible, observers could simulate a subtraction of red from the match side by adding it to the test side

13. Color Models
Method for explaining the properties or behavior of color within some particular context
Combine the light from two or more sources with different dominant frequencies and vary the intensity of light to generate a range of additional colors
Primary Colors
3 primaries are sufficient for most purposes
Hues that we choose for the sources
Color gamut is the set of all colors that we can produce from the primary colors
Complementary color is two primary colors that produce white
Red and Cyan, Green and Magenta, Blue and Yellow

14. Color-Matching
Colors in the vicinity of 500 nm can be matched by subtracting an amount of red light from a combination of blue and green lights
Thus, an RGB color monitor cannot display colors in the neighborhood of 500 nm

15. CIE XYZ Problem solution: XYZ color system
Tristimulus system derived from RGB
Based on 3 imaginary primaries
All 3 primaries are outside the human visual gamut
Only positive XYZ values can occur
1931 by CIE (Commission Internationale de l’Eclairage)

16. Transformation CIE RGB->XYZ
Projective transformation specifically designed so that Y = V (luminous efficiency function)
XYZ  CIE RGB uses inverse matrix
XYZ  any RGB matrix is device dependent
X = 0.723R G B
Y = 0.265R G B
Z = 0.000R G B

17. The XYZ Model CIE primitives is referred to as the XYZ model
In XYZ color space, color C (λ) represented as C (λ) = (X, Y, Z)
where X Y Z are calculated from the color-matching functions
k = 683 lumens/watt
I(λ) = spectral radiance
f = color-matching function

18. The XYZ Model Normalized XYZ values
Normalize the amounts of each primary against the sum X+Y+Z, which represent the total light energy
where z = 1 - x - y, color can be represented with just x and y
x and y called chromaticity value,
it depend only on hue and purify
Y is luminance

19. RGB vs. XYZ

20. The CIE Chromaticity Diagram
A tongue-shape curve formed by plotting the normalized amounts x and y for colors in the visible spectrum
Points along the curve are spectral color (pure color)
Purple line, the line joining the red and violet spectral points
Illuminant C, plotted for a white light source and used as a standard approximation for average daylight
Spectral Colors C
Illuminant
Purple Line

21. The CIE Chromaticity Diagram
Luminance values are not available because of normalization
Colors with different luminance but same chromaticity map to the same point
Usage of CIE chromaticity diagram
Comparing color gamuts for different set of primaries
Identifying complementary colors
Determining purity and dominate wavelength for a given color
Color gamuts
Identify color gamuts on diagram as straight-line segments or polygon regions

22. The CIE Chromaticity Diagram
Color gamuts
All color along the straight line joining C1 and C2 can be obtained by mixing colors C1 and C2
Greater proportion of C1 is used, the resultant color is closer to C1 than C2
Color gamut for C3, C4, C5 generate colors inside or on edges
No set of three primaries can be combined to generate all colors

23. The CIE Chromaticity Diagram
Complementary colors
Represented on the diagram as two points on opposite sides of C and collinear with C
The distance of the two colors C1 and C2 to C determine the amount of each needed to produce white light

24. The CIE Chromaticity Diagram
Dominant wavelength
Draw a straight from C through color point to a spectral color on the curve, the spectral color is the dominant wavelength
Special case: a point between C and a point on the purple line Cp, take the compliment Csp as dominant
Purity
For a point C1, the purity determined as the relative distance of C1 from C along the straight line joining C to Cs
Purity ratio = dC1 / dCs

25. Complementary Colors Subtractive Additive Pair of complementary colors
subYM
Complementary Colors
subCR
Additive
Blue is one-third
Yellow (red+green) is two-thirds
When blue and yellow light are added together, they produce white light
Pair of complementary colors
blue and yellow
green and magenta
red and cyan
Subtractive
Orange (between red and yellow)<>cyan-blue
green-cyan<>magenta-red color
addRG

26. The RGB Color Model Basic theory of RGB color model
The tristimulus theory of vision
It states that human eyes perceive color through the stimulation of three visual pigment of the cones of the retina
Red, Green and Blue
Model can be represented by the unit cube defined on R,G and B axes

27. The RGB Color Model An additive model, as with the XYZ color system
Each color point within the unit cube can be represented as a weighted vector sum of the primary colors, using vectors R, G and B
C(λ)=(R, G, B)=RR+GG+BB
Chromaticity coordinates for the National Television System Committee (NTSC) standard RGB primaries

28. Subtractive RGB Colors
Red
Green
Blue
Yellow
Cyan
Magenta
Black
Yellow absorbs Blue
Magenta absorbs Green
Cyan absorbs Red
White  minus Blue minus Green = Red

29. The CMY and CMYK Color Models
Color models for hard-copy devices, such as printers
Produce a color picture by coating a paper with color pigments
Obtain color patterns on the paper by reflected light, which is a subtractive process
The CMY parameters
A subtractive color model can be formed with the primary colors cyan, magenta and yellow
Unit cube representation for the CMY model with white at origin

30. The CMY and CMYK Color Models
Transformation between RGB and CMY color spaces
Transformation matrix of conversion from RGB to CMY
Transformation matrix of conversion from CMY to RGB

31. The YIQ and Related Color Models
YIQ, NTSC color encoding for forming the composite video signal
YIQ parameters
Y, same as the Y complement in CIE XYZ color space, luminance
Calculated Y from the RGB equations
Y = R G B
Chromaticity information (hue and purity) is incorporated with I and Q parameters, respectively
Calculated by subtracting the luminance from the red and blue components of color
I = R – Y
Q = B – Y
Separate luminance or brightness from color, because we perceive brightness ranges better than color

32. The YIQ and Related Color Models (2)
Transformation between RGB and YIQ color spaces
Transformation matrix of conversion from RGB to YIQ
Transformation matrix of conversion from YIQ to RGB
Obtain from the inverse matrix of the RGB to YIQ conversion

33. The HSV Color Model
Interface for selecting colors often use a color model based on intuitive concepts rather than a set of primary colors
The HSV parameters
Color parameters are hue (H), saturation (S) and value (V)
Derived by relating the HSV parameters to the direction in the RGB cube
Obtain a color hexagon by viewing the RGB cube along the diagonal from the white vertex to the origin

34. The HSV Color Model The HSV hexcone
Hue is represented as an angle about the vertical axis ranging from 0 degree at red to 360 degree
Saturation parameter is used to designate the purity of a color
Value is measured along a vertical axis through center of hexcone

35. HSV Color Model Hexcone
Color components:
Hue (H) ∈ [0°, 360°]
Saturation (S) ∈ [0, 1]
Value (V) ∈ [0, 1]

36. HSV Color Definition Color definition
Select hue, S=1, V=1
Add black pigments, i.e., decrease V
Add white pigments, i.e., decrease S
Cross section of the HSV hexcone showing regions for shades, tints, and tones

37. HSV Hue is the most obvious characteristic of a color
Chroma is the purity of a color
High chroma colors look rich and full
Low chroma colors look dull and grayish
Sometimes chroma is called saturation
Value is the lightness or darkness of a color
Sometimes light colors are called tints, and
Dark colors are called shades

38. Transformation To move from RGB space to HSV space:
Can we use a matrix? No, it’s non-linear.

39. The HSV Color Model Transformation between HSV and RGB color spaces
Procedure for mapping RGB into HSV
class rgbSpace {public: float r, g, b;};
class hlsSpace {public: float h, l, s;};
void hsvT0rgb (hlsSpace& hls, rgbSpace& rgb) {
/* HLS and RGB values are in the range from 0 to 1.0 */
int k
float aa, bb, cc, f;
if ( s <= 0.0)
r = g = b = v; /* Have gray scale if s = 0 */
else {
if (h == 1.0) h = 0.0;
h *= 6.0;
k = floor (h);
f = h - k;
aa = v * (1.0 - s);
bb = v * (1.0 - (s * f));
cc = v * (1.0 - (s * (1.0 - f)));
switch (k) {
case 0: r = v; g = cc; b = aa; break;
case 1: r = bb; g = v; b = aa; break;
case 2: r = aa; g = v; b = cc; break;
case 3: r = aa; g = bb; b = v; break;
case 4: r = cc; g = aa; b = v; break;
case 5: r = v; g = aa; b = bb; break; }

40. The HSV Color Model Transformation between HSV and RGB color spaces
Procedure for mapping HSV into RGB
class rgbSpace {public: float r, g, b;};
class hlsSpace {public: float h, l, s;};
const float noHue = -1.0;
inline float min(float a, float b) {return (a < b)? a : b;}
inline float mab(float a, float b) {return (a > b)? a : b;}
void rgbTOhsv (rgbSpace rgb, hlsSpace hls) {
float minRGB = min (r, min (g, b)), maxRGB = max (r, max (g, b));
float deltaRGB = maxRGB - minRGB;
v = maxRGB;
if (maxRGB != 0.0) s = deltaRGB / maxRGB;
else s = 0.0;
if (s <= 0.0) h = noHue;
else {
if (r == maxRGB) h = (g - b) / deltaRGB; else
if (g == maxRGB)
h = (b - r) / deltaRGB;
else
if (b == maxRGB)
h = (r - g) / deltaRGB;
h *= 60.0;
if (h < 0.0) h += 360.0;
h /= 360.0; }

41. The HLS Color Model HLS color model
Another model based on intuitive color parameter
Used by the Tektronix Corporation
The color space has the double-cone representation
Used hue (H), lightness (L) and saturation (S) as parameters

42. Color Model Summary Colorimetry: Device Color Systems:
CIE XYZ: contains all visible colors
Device Color Systems:
RGB: additive device color space (monitors)
CMYK: subtractive device color space (printers)
YIQ: NTSC television (Y=luminance, I=R-Y, Q=B-Y)
Color Ordering Systems:
HSV, HLS: for user interfaces

43. Comparison
RGB
CMY
CMYK
YIQ
HSV
HSL

44. Color Selection and Applications
Graphical package provide color capabilities in a way that aid users in making color selections
For example, contain sliders and color wheels for RGB components instead of numerical values
Color applications guidelines
Displaying blue pattern next to a red pattern can cause eye fatigue
Prevent by separating these color or by using colors from one-half or less of the color hexagon in the HSV model
Smaller number of colors produces a better looking display
Tints and shades tend to blend better than pure hues
Gray or complement of one of the foreground color is usually best for background

45. How different are the colors of square A and square B?
They are the same!
Don’t believe me?

46. What color is this
blue cube?
How about this
yellow cube?

47. Want to see it slower? What color is this How about this blue cube?
yellow cube?

48. Even slower?
How about this
yellow cube?
What color is this
blue cube?

49. So what color is it? What color is this How about this blue cube?
yellow cube?
It’s gray!

50. Humans Only Perceive Relative Brightness

51. Cornsweet Illusion
Cornsweet illusion. Left part of the picture seems to be darker than the right one. In fact they have the same brightness.
The same image, but the edge in the middle is hidden. Left and right part of the image appear as the same color now.

52. Self-Animated Images

53. What happens when chickens see red?
A company* that markets red contact lenses for chickens (at 20 cents a pair), points to medical studies showing that chickens wearing red-tinted contact lenses behave differently from birds that don't.
They eat less, produce more and don't fight as much. This decreases aggressive tendencies and birds are less likely to peck at each other causing injury.
A spokesman said the lenses will improve world egg-laying productivity by $600 million a year. (Perhaps everything looks red and they cannot distinguish combs, wattles, or blood. Or ...perhaps the chickens are happier because they're viewing the world through rose colored glasses.)
Animalens Inc. of Wellesley, Mass
If you don't believe this, read the facts!

54. What did you see?

55. Bird in a Cage