Speeding-Up Fractal Colored Image Compression Using Moments Features

In this research, new fractal compression technique is introduced. It is based on using moment features to index the zero-mean range on domain blocks. The moment features have been used to speed up the iterated function system (IFS) matching stage. These features are used to determine the block descriptor "moment\´s ratio index", which in turn is utilized to classify the image blocks in both domain and range pools. During the encoding stage the block moment ratio descriptor of each range blocks is used to filter the domain blocks and keep only those blocks whose moment descriptor is suitable to be IFS matched with the tested range block. The data of the color components (R,G,B) are transformed to (Y,U,V) component, to take the advantage of the existing spectral correlation and gain more compression. The results of the tests conducted on Lena (256 times 256) pixel, resolution 24 bits/pixel) image showed a lower encoding time (4.82 sec) with appropriate PSNR (30dB). The time speeding is about (96%) in comparison with that for traditional method.