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Proceedings Paper

Lossy compression of gray-scale document images by adaptive-offset quantization
Author(s): Kris Popat
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Paper Abstract

This paper describes an adaptive-offset quantization scheme and considers its application to the lossy compression of grayscale document images. The technique involves scalar- quantizing and entropy-coding pixels sequentially, such that the quantizer's offset is always chosen to minimize the expected number of bits emitted for each pixel, where the expectation is based on the predictive distribution used for entropy coding. To accomplish this, information is fed back from the entropy coder's statistical modeling unit to the quantizer. This feedback path is absent in traditional compression schemes. Encouraging but preliminary experimental results are presented comparing the technique with JPEG and with fixed-offset quantization on a scanned grayscale text image.

Paper Details

Date Published: 21 December 2000
PDF: 9 pages
Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); doi: 10.1117/12.410832
Show Author Affiliations
Kris Popat, Xerox Palo Alto Research Ctr. (United States)

Published in SPIE Proceedings Vol. 4307:
Document Recognition and Retrieval VIII
Paul B. Kantor; Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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