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Full color image along with its R, G, and B components Additive color mixing demonstrated with CD covers used as beam splitters A diagram demonstrating additive color with RGB. The RGB color model is an additive color model [1] in which the red, green, and blue primary colors of light are added together in various ways to reproduce a broad ...
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For each unique palette, an image color test chart and sample image (truecolor original follows) rendered with that palette (without dithering) are given. The test chart shows the full 256 levels of the red, green, and blue (RGB) primary colors and cyan, magenta, and yellow complementary colors, along with a full 256-level grayscale.
Saturation, or the lack of it, produces tones of the reference hue that converge on the zero-saturation shade of gray, which is determined by the lightness. The following examples uses the hues red, orange, and yellow at midpoint lightness with decreasing saturation. The resulting RGB value and the total intensity is shown.
An example is the 256-color palette commonly used in the GIF file format, in which 256 colors to be used to represent an image are selected from the whole 24 bit color space, each being assigned an 8 bit index. This way, while the system can potentially reproduce any color in the RGB color space (as long as the 256 color restriction allows ...
This image demonstrates the difference between how colors will look on a computer monitor (RGB) compared to how they might reproduce in a particular CMYK print process. Colors can be created in printing with color spaces based on the CMYK color model , using the subtractive primary colors of pigment ( c yan , m agenta , y ellow , and blac k ).
Here is an example of color channel splitting of a full RGB color image. The column at left shows the isolated color channels in natural colors, while at right there are their grayscale equivalences: Composition of RGB from three grayscale images. The reverse is also possible: to build a full-color image from their separate grayscale channels.
A histogram of an image is produced first by discretization of the colors in the image into a number of bins, and counting the number of image pixels in each bin. For example, a Red–Blue chromaticity histogram can be formed by first normalizing color pixel values by dividing RGB values by R+G+B, then quantizing the normalized R and B ...