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Proceedings Paper

Adaptable recursive binary entropy coding technique
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Paper Abstract

We present a novel data compression technique, called recursive interleaved entropy coding, that is based on recursive interleaving of variable-to variable length binary source codes. A compression module implementing this technique has the same functionality as arithmetic coding and can be used as the engine in various data compression algorithms. The encoder compresses a bit sequence by recursively encoding groups of bits that have similar estimated statistics, ordering the output in a way that is suited to the decoder. As a result, the decoder has low complexity. The encoding process for our technique is adaptable in that each bit to be encoded has an associated probability-of-zero estimate that may depend on previously encoded bits; this adaptability allows more effective compression. Recursive interleaved entropy coding may have advantages over arithmetic coding, including most notably the admission of a simple and fast decoder. Much variation is possible in the choice of component codes and in the interleaving structure, yielding coder designs of varying complexity and compression efficiency; coder designs that achieve arbitrarily small redundancy can be produced. We discuss coder design and performance estimation methods. We present practical encoding and decoding algorithms, as well as measured performance results.

Paper Details

Date Published: 30 July 2002
PDF: 15 pages
Proc. SPIE 4736, Visual Information Processing XI, (30 July 2002); doi: 10.1117/12.477575
Show Author Affiliations
Aaron B. Kiely, Jet Propulsion Lab. (United States)
Matthew A. Klimesh, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 4736:
Visual Information Processing XI
Zia-ur Rahman; Robert A. Schowengerdt; Stephen E. Reichenbach, Editor(s)

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