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Proceedings Paper

Integrated wavelet compression and restoration
Author(s): Zia-ur Rahman
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Paper Abstract

The performance of wavelet compression algorithms is generally judged solely as a function of the compression ratio and the vidual artifacts which are perceivable in the reconstructed image. The problem then becomes one of obtaining the best compression with fewest visible artifacts--a very subjective measure. Our wavelet compression algorithm uses an information theoretic analysis for the design of the compression maps. We have previously shown that maximizing the information for a given visual communication channel also maximizes the visual quality of the restored image. We utilize this to design quantization maps which maximize information for a given compression ratio. Hence we are able to design quantization maps which maximize the restorability of an image--i.e. the information content, the image quality, and the mean-square difference fidelity--for a given compression ratio.

Paper Details

Date Published: 23 October 1996
PDF: 10 pages
Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); doi: 10.1117/12.255288
Show Author Affiliations
Zia-ur Rahman, College of William and Mary (United States)

Published in SPIE Proceedings Vol. 2825:
Wavelet Applications in Signal and Image Processing IV
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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