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Wavelet-based image processing
by
James S. Walker
University of Wisconsin-Eau Claire, USA
The 1990's witnessed an explosion of applications of wavelet-based techniques to fundamental problems in image processing, such as compression and denoising. We shall outline the principal reasons for the success of these techniques: the relation of wavelets to vision, and their remarkable structural properties. Wavelets are particularly well-adapted to iterative, multi-resolution, algorithms for compression and denoising, which bear some resemblance to techniques employed by mamallian visual systems. Some important compression and denoising algorithms, e.g. SURESHRINK and JPEG 2000, will be summarized.
Date received: June 27, 2003
Copyright © 2003 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Mathematical Conference Abstracts. Document # calr-59.