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

Daniela Calvetti; Bryan Lewis; Lothar Reichel

doi:10.1117/12.452016

6 December 2002 A hybrid GMRES and TV-norm-based method for image restoration

Daniela Calvetti, Bryan Lewis, Lothar Reichel

Proceedings Volume 4791, Advanced Signal Processing Algorithms, Architectures, and Implementations XII; (2002) https://doi.org/10.1117/12.452016
Event: International Symposium on Optical Science and Technology, 2002, Seattle, WA, United States

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.

Citation Download Citation

Daniela Calvetti, Bryan Lewis, and Lothar Reichel "A hybrid GMRES and TV-norm-based method for image restoration", Proc. SPIE 4791, Advanced Signal Processing Algorithms, Architectures, and Implementations XII, (6 December 2002); https://doi.org/10.1117/12.452016

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