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Proceedings Paper

Binary image compression using conditional entropy-based dictionary design and indexing
Author(s): Yandong Guo; Dejan Depalov; Peter Bauer; Brent Bradburn; Jan P. Allebach; Charles A. Bouman
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Paper Abstract

The JBIG2 standard is widely used for binary document image compression primarily because it achieves much higher compression ratios than conventional facsimile encoding standards, such as T.4, T.6, and T.82 (JBIG1). A typical JBIG2 encoder works by first separating the document into connected components, or symbols. Next it creates a dictionary by encoding a subset of symbols from the image, and finally it encodes all the remaining symbols using the dictionary entries as a reference. In this paper, we propose a novel method for measuring the distance between symbols based on a conditionalentropy estimation (CEE) distance measure. The CEE distance measure is used to both index entries of the dictionary and construct the dictionary. The advantage of the CEE distance measure, as compared to conventional measures of symbol similarity, is that the CEE provides a much more accurate estimate of the number of bits required to encode a symbol. In experiments on a variety of documents, we demonstrate that the incorporation of the CEE distance measure results in approximately a 14% reduction in the overall bitrate of the JBIG2 encoded bitstream as compared to the best conventional dissimilarity measures.

Paper Details

Date Published: 4 February 2013
PDF: 10 pages
Proc. SPIE 8652, Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications, 865208 (4 February 2013); doi: 10.1117/12.2006141
Show Author Affiliations
Yandong Guo, Purdue Univ. (United States)
Dejan Depalov, Hewlett-Packard Co. (United States)
Peter Bauer, Hewlett-Packard Co. (United States)
Brent Bradburn, Hewlett-Packard Co. (United States)
Jan P. Allebach, Purdue Univ. (United States)
Charles A. Bouman, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 8652:
Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu; Alessandro Rizzi, Editor(s)

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