Implementation of wavelet transform image compression algorithms using associative-computing-based DSP chips

Aviram Sariel; Pankaj K. Das; William A. Pearlman

doi:10.1117/12.342931

22 March 1999 Implementation of wavelet transform image compression algorithms using associative-computing-based DSP chips

Aviram Sariel, Pankaj K. Das, William A. Pearlman

Author Affiliations +

Proceedings Volume 3723, Wavelet Applications VI; (1999) https://doi.org/10.1117/12.342931
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Aviram Sariel, Pankaj K. Das, and William A. Pearlman "Implementation of wavelet transform image compression algorithms using associative-computing-based DSP chips", Proc. SPIE 3723, Wavelet Applications VI, (22 March 1999); https://doi.org/10.1117/12.342931

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