Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Approximation BFGS methods for nonlinear image restoration

Language

English

Abstract

We consider the iterative solution of unconstrained minimization problems arising from nonlinear image restoration. Our approach is based on a novel generalized BFGS method for such large-scale image restoration minimization problems. The complexity per step of the method is of O (n log n) operations and only O (n) memory allocations are required, where n is the number of image pixels. Based on the results given in [Carmine Di Fiore, Stefano Fanelli, Filomena Lepore, Paolo Zellini, Matrix algebras in quasi-Newton methods for unconstrained minimization, Numer. Math. 94 (2003) 479-500], we show that the method is globally convergent for our nonlinear image restoration problems. Experimental results are presented to illustrate the effectiveness of the proposed method. © 2008 Elsevier B.V. All rights reserved.

Keywords

Nonlinear image restoration, Optimization, Regularization

Publication Date

2009

Source Publication Title

Journal of Computational and Applied Mathematics

Volume

226

Issue

1

Start Page

84

End Page

91

Publisher

Elsevier

DOI

10.1016/j.cam.2008.05.056

Link to Publisher's Edition

http://dx.doi.org/10.1016/j.cam.2008.05.056

ISSN (print)

03770427

ISSN (electronic)

18791778

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