COLOR THEORY Presented by : Md Ashequr Rahman COSC 5335 – Computer Graphics Date : Oct 29, 2002

Organization of this presentation The nature of color and its numerical descriptions Examine some standards Various color models Methods for reducing the number of colors in an image

What Is Color? Aspect of vision – Physical response consisting of the physical reaction of the eye. Can we touch the color? Source of Color – light What is light? Light is an electromagnetic phenomenon. Self propagated electromagnetic wave.

Electromagnetic Spectrum

Retina – Two preceptor 1. Cones  Color sensitive 6 to 714 has its own nerve cell Foeva  all cones concentrated her 2. Rodes  neither distinguish nor see fine details, surrounding foeva. Job – very sensitive to low levels of light. We can see at dim light. How do we see color?

Spectra for some pure colors

Some Definitions Hue : When we call an object "red," we are referring to its hue. Saturation : The saturation of color is a measurement of its purity or how much it has been diluted by white.

Brightness: Brightness refers to the amount of light the color reflects, or how much black is in the color Contrast: Contrast is a measure of the rate of change of brightness in an image. Very high contrast, for example, indicates both dark black and bright white content within the picture.

Total Power in the light, L = (D-A)B+AW Percentage of luminance, purity = ((D-A)B/L)100%

How will we describe a color ? Color Matching By comparing with a set of standard color samples and finding the closest match.

What do we mean = and + in color? What is “ pure spectral color” A totally saturated color having its power concentrated at a single wave length – 100% saturated at. mono( ) = r( )R+ g(x)G+b( )B C = 0.7R+0.5G-0.2B at = 520 Scaling – r( ) + g( )+ b( ) =1

Pure spectral color curve for the RGB Primaries

Standardization- Difficulties – what primary colors are to be used? CIE definition : for primary color x, y and z - are not corresponds to real color - All real color can be presented as positive combination of x, y and z mono( ) = x( )X+y( )Y+ z(- )Z and color matching functions x’( ) = x( )/(x( ) + y( ) +z( ) ) CIE (International commission on ILLUMINATION standard)

1. Wavelength function 2. Pure spectral color curve

Constructing CIE chart -Two dimensional A curve s’( ) = (x’( ), y’( )) pont c (x,y) = (0.313, 0.329) ”white hot” temp 6,504 o C little greater than C

Use of CIE chromaticity diagram 1. Any color on a straight line can be generated by shining various amount of color a & b on the screen. 2. Complementary color can be found f  e with respect to w. 3. Dominant wave length can be found. 4. Saturation or purity can be calculated gw /hw for g.

Color Gamuts Range of color that can be produced on a device

Color Spaces CIE is precise and standard but not natural. Color concept : computer graphics people - RGB other people – hue, sat and lightness Artist – tints, shade, tones

Maping (r,g,b) = (x,y,z)

Additive and subtractive color system (r,g,b) RGB = (1,1,1) – (c,m,y)CMY

HLS Color Model

HSB Color Model

1. Some display unable to handle more than 24 bit colors 2. True color image takes huge memory Substitution Best color Closest color Color quantization

Uniform Quantization

2. Population Algorithm Highest frequency K color of N is replaced 3.Median Cut Algorithm

Octree Quantization

Conclusion: 1. Color is three dimensional, so we need method for describing colors through a triple of numbers. 2. The CIE standard provides a precise approach to specify colors 3. Some color methods converts color to another mehod by using CIE chart 4. Color quantization very difficult to program and their efficiency depends on computational efficiency, and quality of the final image they can produce.

Reference: 1. F.S Hill, Jr. Computer Graphics. 2 nd ed. 2001, prentice Hall 2. Kodak Digital learning Center. sep, Lawise A – Color theory, 1998 – 4. George atto – Color theory & 2D image representation, Aug 29, 200, center of academic computing. publicationscacguide/

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