High-order context modeling and embedded conditional entropy coding of wavelet coefficients for image compression

Much of the progress in wavelet image compression came from better context modeling and entropy coding of quantized wavelet coefficients. In the past few months many papers on the subject were published. They reported rate-distortion performance results that are the best or near the best in the lite...

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Bibliographic Details
Published inConference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136) Vol. 2; pp. 1378 - 1382 vol.2
Main Author Xiaolin Wu
Format Conference Proceeding
LanguageEnglish
Published IEEE 1997
Subjects
Arithmetic
Context modeling
Entropy coding
Image coding
Quantization
Rate-distortion
Shape
Wavelet coefficients
Wavelet domain
Wavelet transforms
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Summary:Much of the progress in wavelet image compression came from better context modeling and entropy coding of quantized wavelet coefficients. In the past few months many papers on the subject were published. They reported rate-distortion performance results that are the best or near the best in the literature. Given seemingly ever smaller improvements on R-D performance with increasing sophistication and complexity of current R-D optimized quantizers and context models of wavelet coefficients, two tantalizing questions are whether there still exists some room for even higher coding efficiency of wavelet image coders, and if so, whether the improvement can be made with an embedded code stream. This paper sheds some lights on, and offers modestly encouraging answers to these questions.
ISBN:9780818683169
0818683163
ISSN:1058-6393
DOI:10.1109/ACSSC.1997.679129