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Statistical modeling of Huffman tables coding

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2005) 3617 LNCS 711-718
DOI: 10.1007/11553595_87
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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). © Springer-Verlag Berlin Heidelberg 2005.

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APA

Battiato, S., Bosco, C., Bruna, A., Di Blasi, G., & Gallo, G. (2005). Statistical modeling of Huffman tables coding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3617 LNCS, pp. 711–718). https://doi.org/10.1007/11553595_87

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