Parallel Pipelined Fractal Image Compression using Quadtree Recomposition

In this paper we present a model and experimental results for performing parallel fractal image compression using circulating pipeline computation and employing a new quadtree recomposition approach. A circular linear array of processors is employed and utilized in a pipelined fashion. In this approach, a modification of the scheme given by Jackson and Blom, quadtree sub-blocks of an image are iteratively recombined into larger blocks for fractal coding. For complex images, this approach exhibits superior parallel runtime performance when compared to a classical quadtree decomposition scheme for fractal image compression, while maintaining high fidelity for reconstructed images. Quantitative results include parallel runtime comparisons with the decomposition approach for several images of varying complexity, an evaluation of attained compression ratios and SNR for reconstructed images. Experimental results using an nCUBE-2 supercomputer are presented.