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Abstract
The principle of fractal image coding is that the image converges to a stable image by iterating the contractive transformations on an arbitrary initial image. This algorithm Partition the image into a number of range blocks and domain blocks. For every range block, the best matching domain block is searched for among all domain blocks by performing a set of transformations on each block. For color image compression, the Fractal coding is applied on different planes of color image independently by treating each plane as gray level image. The coordinate systems used for color image are RGB, YIQ and YUV. To encode a color image the main idea is to divide the image into its three different layers or components (RGB, YIQ and YUV). It is then possible to compress each of these layers separately, handle each of the layers as an independent image. In this paper the data of the color component (R,G,B) are transformed two times in two program separately, ones for YIQ and other for YUV color space. The results show that using (YUV) color space is more useful and efficient than using YIQ in fractal image compression, where PSNR increase 0.1% , CR increase 0.31% and ET decrease 2.321%.
Highlights
Colors are important for human for communicating with the daily encountered objects as well as his species, these colors should be represented formally and numerically within a mathematical formula so it can be projected on device computer storage and applications, this mathematical representation is known as color model that can hold the color space, by the means of color’s primary components (Red, Green, and Blue) the computer can visualizes what the human does in hue and lightness
Most of these techniques reduce the redundancies between color components by transforming the color primaries into a decorrelated color model such as YUV and YIQ. [1]
After the generation of the range and domain pools; one takes each range block listed in the range pool and map it with all the domain blocks listed in the domain pool
Summary
Colors are important for human for communicating with the daily encountered objects as well as his species, these colors should be represented formally and numerically within a mathematical formula so it can be projected on device computer storage and applications, this mathematical representation is known as color model that can hold the color space, by the means of color’s primary components (Red, Green, and Blue) the computer can visualizes what the human does in hue and lightness Most of these techniques reduce the redundancies between color components by transforming the color primaries into a decorrelated color model such as YUV and YIQ. Al-Hilo [2007] has studied speeding fractal color image compression by moment feature includes converting the RGB model system to YUV model and minimize of the rang of U and V because of most of the image data are concentrated in the range of Y [6]
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