Low-complexity waveform coding via alphabet and sample-set partitioning

Amir Said; William A. Pearlman

doi:10.1117/12.263240

10 January 1997 Low-complexity waveform coding via alphabet and sample-set partitioning

Amir Said, William A. Pearlman

Proceedings Volume 3024, Visual Communications and Image Processing '97; (1997) https://doi.org/10.1117/12.263240
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

Abstract

We propose a new low-complexity entropy-coding method to be used for coding waveform signals. It is based on the combination of two schemes: (1) an alphabet partitioning method to reduce the complexity of the entropy-coding process; (2) a new recursive set partitioning entropy-coding process that achieves rates smaller than first order entropy even with fast Huffman adaptive codecs. Numerical results with its application for lossy and lossless image compression show the efficacy of the new method, comparable to the best known methods.

Citation Download Citation

Amir Said and William A. Pearlman "Low-complexity waveform coding via alphabet and sample-set partitioning", Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); https://doi.org/10.1117/12.263240

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