Name
Abstract | ||
|---|---|---|
Image restoration models based on total variation (TV) have become popular since their introduction by Rudin, Osher, and Fatemi
(ROF) in 1992. The dual formulation of this model has a quadratic objective with separable constraints, making projections
onto the feasible set easy to compute. This paper proposes application of gradient projection (GP) algorithms to the dual
formulation. We test variants of GP with different step length selection and line search strategies, including techniques
based on the Barzilai-Borwein method. Global convergence can in some cases be proved by appealing to existing theory. We also
propose a sequential quadratic programming (SQP) approach that takes account of the curvature of the boundary of the dual
feasible set. Computational experiments show that the proposed approaches perform well in a wide range of applications and
that some are significantly faster than previously proposed methods, particularly when only modest accuracy in the solution
is required. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s10589-008-9225-2 | Computational Optimization and Applications |
Keywords | Field | DocType |
Image denoising,Constrained optimization,Gradient projection | Algorithm,Quadratic equation,Duality (optimization),Gradient projection,Image denoising,Image restoration,Mathematics,Constrained optimization | Journal |
Volume | Issue | ISSN |
47 | 3 | 0926-6003 |
Citations | PageRank | References |
57 | 2.38 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingqiang Zhu | 1 | 57 | 2.72 |
| S. J. Wright | 2 | 4391 | 372.21 |
| Tony F. Chan | 3 | 8733 | 659.77 |