DigitalVideoAndHDTVAlgorithmsAndInterfaces.pdf

Linear-Light
Tristimulus
Image Coding Systems
[x, y]
Chromaticity
CIE xyY
Perceptually
Uniform
Nonlinear
Y’C B C R , Y’P B P R ,
Y’UV, Y’IQ
Hue-
Oriented
PROJECTIVE
CIE L*u*v*
TRANSFORM
NONLINEAR
TRANSFORM
RECT./POLAR
CIE L*c*uvhuv
CIE XYZ
NONLINEAR
TRANSFORM
CIE L*a*b*
RECT./POLAR CIE L*c*abhab
3 × 3 AFFINE
TRANSFORM
Linear RGB
TRANSFER
FUNCTION
Nonlinear
R’G’B’
3 × 3 AFFINE
TRANSFORM
NONLINEAR
TRANSFORM
NONLINEAR
TRANSFORM ?
HSB, HSI,
HSL, HSV, } IHS
Figure 21.11 Color systems are classified into four groups that are related by different kinds of
transformations. Tristimulus systems, and perceptually uniform systems, are useful for image
coding. (I flag HSB, HSI, HSL, HSV, and IHS with a question mark: These systems lack objective
definition of color.)
Color image coding
A color image is represented as an array of pixels, where
each pixel contains three values that define a color. As
you have learned in this chapter, three components are
necessary and sufficient to define any color. (In printing
it is convenient to add a fourth, black, component,
giving CMYK.)
In theory, the three numerical values for image coding
could be provided by a color specification system.
However, a practical image coding system needs to be
computationally efficient, cannot afford unlimited precision,
need not be intimately related to the CIE system,
and generally needs to cover only a reasonably wide
range of colors and not all possible colors. So image
coding uses different systems than color specification.
The systems useful for image coding are linear RGB;
nonlinear RGB (usually denoted R’G’B’, and including
sRGB); nonlinear CMY; nonlinear CMYK; and derivatives
of R’G’B’, such as Y’C BC R and Y’P BP R. These are
summarized in Figure 21.11.
230 DIGITAL VIDEO AND HDTV ALGORITHMS AND INTERFACES