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%.

Eman A. Al-Hilo and Rusul Zehwar, “Comparison Fractal Color Image Compression using YIQ and YUV Color Model” International Journal of Advanced Computer Science and Applications(IJACSA), 6(5), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060518

@article{Al-Hilo2015,
title = {Comparison Fractal Color Image Compression using YIQ and YUV Color Model},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060518},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060518},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {5},
author = {Eman A. Al-Hilo and Rusul Zehwar}
}