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Proceedings Paper

Large-scale optimization techniques for nonnegative image restorations
Author(s): Marielba Rojas; Trond Steihaug
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Paper Abstract

We describe an optimization method for large-scale nonnegative regularization. The method is an interior-point iteration that requires the solution of a large-scale and possibly ill-conditioned parameterized trust-region subproblem at each step. The method relies on recently developed techniques for the large-scale trust-region subproblem. We present preliminary numerical results on image restoration problems.

Paper Details

Date Published: 6 December 2002
PDF: 10 pages
Proc. SPIE 4791, Advanced Signal Processing Algorithms, Architectures, and Implementations XII, (6 December 2002); doi: 10.1117/12.452008
Show Author Affiliations
Marielba Rojas, Wake Forest Univ. (United States)
Trond Steihaug, Univ. of Bergen (Norway)

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

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