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Proceedings Paper

A new approach to JBIG2 binary image compression
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Paper Abstract

The JBIG2 binary image encoder dramatically improves compression ratios over previous encoders. The effectiveness of JBIG2 is largely due to its use of pattern matching techniques and symbol dictionaries for the representation of text. While dictionary design is critical to achieving high compression ratios, little research has been done in the optimization of dictionaries across stripes and pages. In this paper we propose a novel dynamic dictionary design that substantially improves JBIG2 compression ratios, particularly for multi-page documents. This dynamic dictionary updating scheme uses caching algorithms to more effciently manage the symbol dictionary memory. Results show that the new dynamic symbol caching technique outperforms the best previous dictionary construction schemes by between 13% and 46% for lossy compression when encoding multi-page documents. In addition, we propose a fast and low-complexity pattern matching algorithm that is robust to substitution errors and achieves high compression ratios.

Paper Details

Date Published: 29 January 2007
PDF: 12 pages
Proc. SPIE 6493, Color Imaging XII: Processing, Hardcopy, and Applications, 649305 (29 January 2007); doi: 10.1117/12.711693
Show Author Affiliations
Maribel Figuera, Purdue Univ. (United States)
Jonghyon Yi, Samsung Electronics (South Korea)
Charles A. Bouman, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 6493:
Color Imaging XII: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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