Context quantization by minimum adaptive code length

Søren Forchhammer, Xiaolin Wu

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Abstract

Context quantization is a technique to deal with the issue of context dilution in high-order conditional entropy coding. We investigate the problem of context quantizer design under the criterion of minimum adaptive code length. A property of such context quantizers is derived for binary symbols. A fast context quantizer design algorithm for conditioning binary symbols is presented and its complexity analyzed. It is conjectured that this algorithm is optimal. The context quantization is performed in what may be perceived as a probability simplex space rather than in the space of context instances.
Original languageEnglish
Title of host publicationIEEE International Symposium on Information Theory, 2007. ISIT 2007.
Number of pages2975
Place of PublicationNice, France
PublisherIEEE
Publication date2007
Pages246-250
ISBN (Print)14-24-41397-3
DOIs
Publication statusPublished - 2007
EventIEEE International Symposium on Information Theory, 2007. - Nice, France
Duration: 1 Jan 2007 → …

Conference

ConferenceIEEE International Symposium on Information Theory, 2007.
CityNice, France
Period01/01/2007 → …

Bibliographical note

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