Name
Abstract | ||
|---|---|---|
We consider the image denoising problem using total variation TV regularization. This problem can be computationally challenging to solve due to the non-differentiability and non-linearity of the regularization term. We propose an alternating direction augmented Lagrangian ADAL method, based on a new variable splitting approach that results in subproblems that can be solved efficiently and exactly. The global convergence of the new algorithm is established for the anisotropic TV model. For the isotropic TV model, by doing further variable splitting, we are able to derive an ADAL method that is globally convergent. We compare our methods with the split Bregman method [T. Goldstein and S. Osher, The split Bregman method for l1-regularized problems, SIAM J. Imaging Sci. 2 2009, pp. 323],which is closely related to it, and demonstrate their competitiveness in computational performance on a set of standard test images. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1080/10556788.2014.955100 | Optimization Methods and Software |
Keywords | Field | DocType |
total variation denoising,augmented lagrangian method,image restoration,total variation regularization,augmented lagrangian,total variation,direct method | Convergence (routing),Isotropy,Mathematical optimization,Anisotropy,Total variation denoising,Regularization (mathematics),Augmented Lagrangian method,Bregman method,Image denoising,Mathematics | Journal |
Volume | Issue | ISSN |
30 | 3 | 1055-6788 |
Citations | PageRank | References |
13 | 0.57 | 26 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwei (Tony) Qin | 1 | 221 | 12.04 |
| Donald Goldfarb | 2 | 868 | 72.71 |
| Shiqian Ma | 3 | 1068 | 63.48 |