An efficient parallel algorithm for hexagonal-based fractal image compression

Abstract

A two-level fast search algorithm to reduce the encoding time for hexagonal-based fractal image compression is presented. The design of the sequential algorithm is based on the distribution of matched domains in a given image. The first search level previews various portions of the image and identifies promising domains among all possible domains. The second search level picks out domain blocks in the image portion where the first level gives positive results, and compares them with a given range block for encoding. The algorithm is parallelized by a dynamic range distribution scheme to achieve load balancing. Experimental results show that by running the parallelized encoding algorithm on multiple processors, the encoding time is drastically reduced while the quality of image reconstruction is retained. A speed-up of about 9 can be obtained by using 13 processors.