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Proceedings Paper

Lossy encoding of document images with the continuous skeleton
Author(s): Jonathan W. Brandt; V. Ralph Algazi
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Paper Abstract

We examine a new approach to document image compression based on the continuous skeleton shape representation. In particular, we exploit the structure-extracting property of the skeleton transformation to devise a code which allows graceful degradation of reproduction quality in exchange for dramatic increases in compression. At the source, the contours which make up the skeleton-based shape description are approximated by B-spline functions and then quantized and encoded. At the receiver, the skeleton contours are reconstructed and then used to regenerate the document. We apply the method to a standard ensemble of facsimile documents and compare the compression results with conventional lossless methods. The result is that significant compression gains can be achieved while incurring nearly imperceptible loss in the reproduction. This approach is motivated by the principle that the proper level at which to encode a document is at the object or component level, rather than at the pixel level. Approximations made to the descriptions of these objects are much less noticeable than comparable approximations made to the raw pixel data. Thus, adopting this object-centered viewpoint toward document compression allows us to introduce errors progressively, and often unobtrusively.

Paper Details

Date Published: 1 November 1992
PDF: 11 pages
Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); doi: 10.1117/12.131481
Show Author Affiliations
Jonathan W. Brandt, Univ. of California/Davis (United States)
V. Ralph Algazi, Univ. of California/Davis (United States)

Published in SPIE Proceedings Vol. 1818:
Visual Communications and Image Processing '92
Petros Maragos, Editor(s)

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