A Fast-speed Fractal Image Compression Algorithm Based on Eigenvalue Pre-searching

Abstract

Fractal coding is a very promising technique for image compression. However, its major drawback is the high encoding complexity to find the best match between a range block and a large pool of domain blocks. This paper presents a fractal-encoding algorithm based on eigenvalue pre-searching. The number of domain blocks searched to find the best match for each range block is safely reduced by eliminating the domain blocks whose eigenvalues are not similar with those of the range block. Simulation results show that the proposed algorithm can produce an almost completely identical fractal code to that of the exhaustive search in reduced time. The proposed scheme promotes an 84.4% reduction in encoding time comparing to the baseline fractal-coding scheme with a little PSNR reduction from 32.8dB to 30.1dB in case of 15 candidates after pre-searching. For single candidate case, the proposed scheme can reduce the complexity up to 85.3%. The compression rate is 12.2 in spite of the number of candidates.