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2010

Fast Image Recovery Using Variable Splitting and Constrained Optimization

8 years 3 months ago
Fast Image Recovery Using Variable Splitting and Constrained Optimization
We propose a new fast algorithm for solving one of the standard formulations of image restoration and reconstruction which consists of an unconstrained optimization problem where the objective includes an 2 data-fidelity term and a nonsmooth regularizer. This formulation allows both wavelet-based (with orthogonal or frame-based representations) regularization or total-variation regularization. Our approach is based on a variable splitting to obtain an equivalent constrained optimization formulation, which is then addressed with an augmented Lagrangian method. The proposed algorithm is an instance of the so-called alternating direction method of multipliers, for which convergence has been proved. Experiments on a set of image restoration and reconstruction benchmark problems show that the proposed algorithm is faster than the current state of the art methods.
Manya V. Afonso, José M. Bioucas-Dias, M&aa
Added 22 May 2011
Updated 22 May 2011
Type Journal
Year 2010
Where TIP
Authors Manya V. Afonso, José M. Bioucas-Dias, Mário A. T. Figueiredo
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