Restoration of images based on subspace optimization accelerating augmented Lagrangian approach

Authors:
Dai-Qiang Chen;Li-Zhi Cheng;Fang Su
Affiliations:
-;-;-
Venue:
Journal of Computational and Applied Mathematics
Year:
2011

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Abstract

We propose a new fast algorithm for solving a TV-based image restoration problem. Our approach is based on merging subspace optimization methods into an augmented Lagrangian method. The proposed algorithm can be seen as a variant of the ALM (Augmented Lagrangian Method), and the convergence properties are analyzed from a DRS (Douglas-Rachford splitting) viewpoint. Experiments on a set of image restoration benchmark problems show that the proposed algorithm is a strong contender for the current state of the art methods.