Statistical Modeling of Huffman Tables Coding

  • S. Battiato
  • C. Bosco
  • A. Bruna
  • G. Di Blasi
  • G. Gallo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

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).

Keywords

Standard Code Input Dataset Lossless Compression Standard Table Semantic Classis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • S. Battiato
    • 1
  • C. Bosco
    • 1
  • A. Bruna
    • 2
  • G. Di Blasi
    • 1
  • G. Gallo
    • 1
  1. 1.D.M.I.University of CataniaCataniaItaly
  2. 2.AST Catania LabSTMicroelectronics 

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