Implementation of wavelet transform image compression algorithms using associative-computing-based DSP chips
Aviram Sariel, Pankaj Kumar Das, William A. Pearlman · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1999
Wavelet Transform is known to produce the most effective and computational efficient technique for image compression. The optimum space-spatial frequency localization property of this transform is utilized in the Embedded Zero Tree Wavelet Coding which has been refined to produce best performance in SPIHT (set partitioning in the hierarchical trees) algorithm for lossy compression and S+P (S-transform and prediction) for lossless compression. Using the multi- resolution property of wavelet transform one can also have progressive transmission for preliminary inspection where the criterion for progressiveness could be either fidelity or resolution. The three important points of wavelet based compression algorithms are: (1) partial ordering of transformed magnitudes with order transmission using subset partitioning, (2) refinement bit transmission using ordered bit plane, and (3) use of the self-similarity of the transform coefficients for different scales.