Color image processing and color models


Color image processing
The use of color in image processing is motivated by two principal factors:
1. The fact that color is a powerful descriptor it often simplifies object identification and extraction from a given scene
2. A human can discern thousands of colors shades and intensities, compared to about only a few dozens of shades of gray.

Characterizing colors
The characteristics generally used to distinguish one color from another are:
1. Hue:
Hue is an attribute associated with the dominant wavelength in a mixture of white light. It represents the dominant color as perceived by the observer.
2. Saturation:
Saturation refers to the relative purity or amount of white light mixed with a hue. The pure spectrum colors are fully saturated. Colors such as pink (red + white) are less saturated, with degree of saturation being inversely proportional to the amount of white light added.
3. Brightness:
Brightness refers to the intensity of light.

Hue and saturation together are called chromaticity, and therefore, a color may be characterized by its brightness and chromaticity.

Color models:
The color models (also called color space or color system) facilitate the specification of colors in some standard or generally accepted way.
Different color models available are:
1. RGB
2. CMY(CMYK)
3. HSI
4. HSV
5. YIQ
6. YUV(YCbCr)

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