Statistical modeling of huffman tables coding

Authors:
S. Battiato;C. Bosco;A. Bruna;G. Di Blasi;G. Gallo
Affiliations:
D.M.I., University of Catania, Catania, Italy;D.M.I., University of Catania, Catania, Italy;AST Catania Lab, STMicroelectronics;D.M.I., University of Catania, Catania, Italy;D.M.I., University of Catania, Catania, Italy
Venue:
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Year:
2005

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Abstract

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).