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Proceedings Paper

Efficient arithmetic coding for wavelet image compression
Author(s): Zixiang Xiong; Kannan Ramchandran; Michael T. Orchard
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Paper Abstract

We address efficient context modeling in arithmetic coding for wavelet image compression. Quantized highpass wavelet coefficients are first mapped into a binary source, followed by high order context modeling in arithmetic coding. A blending technique is used to combine results of context modeling of different orders into a single probability estimate. Experiments show that an arithmetic coder with efficient context modeling is capable of achieving a 10% bitrate saving (or 0.5 dB gain in PSNR) over a zeroth order adaptive arithmetic coder in high performance wavelet image coders.

Paper Details

Date Published: 10 January 1997
PDF: 12 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263294
Show Author Affiliations
Zixiang Xiong, Princeton Univ. (United States)
Kannan Ramchandran, Univ. of Illinois/Urbana-Champaign (United States)
Michael T. Orchard, Princeton Univ. (United States)


Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp, Editor(s)

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