A parallel fractal image compression algorithm for hypercube multiprocessors

Data compression has become an important issue in relation to storage and transmission. This issue is especially true for databases consisting of a large number of detailed computer images. Many methods have been proposed in recent years for achieving high compression ratios for compressed image storage. A very promising compression technique, in terms of compression ratios, is fractal image compression. Fractal image compression exploits natural affine redundancy present in typical images to achieve a high compression ratio in a lossy compression format. Fractal based compression algorithms, however, have high computational demands. To obtain faster compression, a sequential fractal image compression algorithm may be translated into a parallel algorithm. This translation takes advantage of the inherently parallel nature, from a data domain viewpoint, of the fractal transform process