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Proceedings Paper

Image compression with QM-AYA adaptive binary arithmetic coder
Author(s): Joe-Ming Cheng; Glen G. Langdon
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Paper Abstract

The Q-coder has been reported in the literature, and is a renorm-driven binary adaptive arithmetic coder. A similar renorm-driven coder, the QM coder, uses the same approach with an initial attack to more rapidly estimate the statistics in the beginning, and with a different state table. The QM coder is the adaptive binary arithmetic coder employed in the JBIG and JPEG image compression algorithms. The QM-AYA arithmetic coder is similar to the QM coder, with a different state table, that offers balanced improvements to the QM probability estimation for the less skewed distributions. The QM-AYA performs better when the probability estimate is near 0.5 for each binary symbol. An approach for constructing effective index change tables for Q-coder type adaptation is discussed.

Paper Details

Date Published: 12 January 1993
PDF: 11 pages
Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); doi: 10.1117/12.139086
Show Author Affiliations
Joe-Ming Cheng, ADSTAR (United States)
Glen G. Langdon, Univ. of California/Santa Cruz and IBM Almaden Research Ctr. (United States)


Published in SPIE Proceedings Vol. 1771:
Applications of Digital Image Processing XV
Andrew G. Tescher, Editor(s)

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