Massively Parallel Processing Approach to Fractal Image Compression

In the last years Image Fractal Compression techniques (IFS) have gained ever more interest because of their capability to achieve high compression ratios while maintaining very good quality for the reconstructed image. The main drawback of such techniques is the very high computing time needed to determine the compressed code. In this paper, after a brief description of the IFS theory, we discuss its parallel implementation by comparing the different level of exploitable parallelism. In the paper we show that Massively Parallel Processing on SIMD machines is the best way to use all the large granularity parallelism present in this problem. Finally, we give some results achieved implementing IFS compression technique on the MPP APE 1 OO/Quadrics machine.