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Proceedings Paper

A hybrid GMRES and TV-norm-based method for image restoration
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Paper Abstract

Total variation-penalized Tikhonov regularization is a popular method for the restoration of images that have been degraded by noise and blur. The method is particularly effective, when the desired noise- and blur-free image has edges between smooth surfaces. The method, however, is computationally expensive. We describe a hybrid regularization method that combines a few steps of the GMRES iterative method with total variation-penalized Tikhonov regularization on a space of small dimension. This hybrid method requires much less computational work than available methods for total variation-penalized Tikhonov regularization and can produce restorations of similar quality.

Paper Details

Date Published: 6 December 2002
PDF: 9 pages
Proc. SPIE 4791, Advanced Signal Processing Algorithms, Architectures, and Implementations XII, (6 December 2002); doi: 10.1117/12.452016
Show Author Affiliations
Daniela Calvetti, Case Western Reserve Univ. (United States)
Bryan Lewis, Rocketcalc, LLC (United States)
Lothar Reichel, Kent State Univ. (United States)

Published in SPIE Proceedings Vol. 4791:
Advanced Signal Processing Algorithms, Architectures, and Implementations XII
Franklin T. Luk, Editor(s)

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