Speeding-up fractal colored image using moments features

In this research, new fractal compression technique is introduced based on using moment features to block indexing the zero-mean range-domain blocks. The moment features have been used to speed up the IFS-matching stage. These features are used to determine the descriptor ldquoblock moments ratio indexrdquo, which in turn utilized to classify the image blocks in both domain and range blocks. To encode each range block, its moments ratio descriptor is used to filter the domain blocks and keep only the blocks that are suitable to be IFS matched with 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 tests conducted on Lena (256times256 pixel, resolution 24 bits/pixel) image showed a minimum encoding time (4.82 sec) with appropriate PSNR (30 dB). The speeding is about (96%) in comparison with that for traditional method.