Algorithms and software for total variation image reconstruction via first-order methods

被引：121

作者：

Dahl, Joachim ^{[2
]}

Hansen, Per Christian ^{[1
]}

Jensen, Soren Holdt ^{[3
]}

Jensen, Tobias Lindstrom ^{[3
]}

机构：

[1] Tech Univ Denmark, Dept Informat & Math Modelling, DK-2800 Lyngby, Denmark

[2] AnyBody Technol AS, DK-9220 Aalborg O, Denmark

[3] Aalborg Univ, Dept Elect Syst, DK-9220 Aalborg O, Denmark

来源：

NUMERICAL ALGORITHMS | 2010年 / 53卷 / 01期

关键词：

Total variation; Denoising; Inpainting; Deblurring; First-order methods; Matlab; TOTAL VARIATION MINIMIZATION; CONSTRAINED TOTAL VARIATION;

D O I：

10.1007/s11075-009-9310-3

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper describes new algorithms and related software for total variation (TV) image reconstruction, more specifically: denoising, inpainting, and deblurring. The algorithms are based on one of Nesterov's first-order methods, tailored to the image processing applications in such a way that, except for the mandatory regularization parameter, the user needs not specify any parameters in the algorithms. The software is written in C with interface to Matlab (version 7.5 or later), and we demonstrate its performance and use with examples.

引用

页码：67 / 92

页数：26

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