REGION-BASED FRACTAL IMAGE COMPRESSION USING HEURISTIC-SEARCH

This paper presents work carried out on fractal (or attractor) image c ompression. The approach relies on the assumption that image redundanc y can be efficiently exploited through self-transformability. The algo rithms described in this paper utilize a novel region-based partition of the image that greatly increases the compression ratios achieved ov er traditional block-based partitionings. Due to the large search spac es involved, heuristic algorithms are used to construct these region-b ased transformations. Results for three different heuristic algorithms are given. The results show that the region-based system achieves alm ost double the compression ratio of the simple block-based system at a similar decompressed image quality. For the Lena Image, compression r atios of 41:1 can be achieved at a PSNR of 26.56 dB.