2005 | OriginalPaper | Buchkapitel
Statistical Modeling of Huffman Tables Coding
verfasst von : S. Battiato, C. Bosco, A. Bruna, G. Di Blasi, G. Gallo
Erschienen in: Image Analysis and Processing – ICIAP 2005
Verlag: Springer Berlin Heidelberg
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An innovative algorithm for automatic generation of Huffman coding tables for semantic classes of digital images is presented. Collecting statistics over a large dataset of corresponding images, we generated Huffman tables for three images classes: landscape, portrait and document. Comparisons between the new tables and the JPEG standard coding tables, using also different quality settings, have shown the effectiveness of the proposed strategy in terms of final bit size (e.g. compression ratio).