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Proceedings Paper

Implementation of wavelet transform image compression algorithms using associative-computing-based DSP chips
Author(s): Aviram Sariel; Pankaj K. Das; William A. Pearlman
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Paper 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.

Paper Details

Date Published: 22 March 1999
PDF: 15 pages
Proc. SPIE 3723, Wavelet Applications VI, (22 March 1999); doi: 10.1117/12.342931
Show Author Affiliations
Aviram Sariel, Associative Computing, Ltd. (Israel)
Pankaj K. Das, Rensselaer Polytechnic Institute (United States)
William A. Pearlman, Rensselaer Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 3723:
Wavelet Applications VI
Harold H. Szu, Editor(s)

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