Paper
19 April 2000 Wavelet image coding using intercontext arithmetic adaptation
Nikolaos V. Boulgouris, Dimitrios Vyzovitis, Michael G. Strintzis
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Abstract
In this paper, we present a novel approach to overcoming the context dilution problem in context-based entropy coding of images. We propose a family of algorithms that employ similarity among context models to improve the adaptation rate of context models. The proposed scheme employs nonconventional updates of the probability tables kept by the context entropy coder, that extend the notion of symbol occurrence. Preliminary experimental results, obtained using wavelet transformed images, indicate that the basic algorithm indeed improves the performance of conventional context modelers by enhancing the model adaptation rate, and achieve efficiency competitive to well-established algorithms.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nikolaos V. Boulgouris, Dimitrios Vyzovitis, and Michael G. Strintzis "Wavelet image coding using intercontext arithmetic adaptation", Proc. SPIE 3974, Image and Video Communications and Processing 2000, (19 April 2000); https://doi.org/10.1117/12.382998
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KEYWORDS
Image compression

Wavelets

Image filtering

Computer programming

Performance modeling

Wavelet transforms

Medical imaging

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