Classification Based Speed-Up Methods for Fractal Image Compression on Multicomputers
ParNum '99 Proceedings of the 4th International ACPC Conference Including Special Tracks on Parallel Numerics and Parallel Computing in Image Processing, Video Processing, and Multimedia: Parallel Computation
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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.