Name
Title | ||
|---|---|---|
Restoration of images based on subspace optimization accelerating augmented Lagrangian approach |
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.cam.2010.11.028 | J. Computational Applied Mathematics |
Keywords | Field | DocType |
convergence property,strong contender,new fast algorithm,art method,image restoration benchmark problem,augmented lagrangian method,douglas-rachford splitting,tv-based image restoration problem,augmented lagrangian approach,proposed algorithm,subspace optimization,current state,image restoration,augmented lagrangian,total variation | Convergence (routing),Mathematical optimization,Subspace topology,Calculus of variations,Augmented Lagrangian method,Image restoration,Lagrangian relaxation,Merge (version control),Numerical analysis,Mathematics | Journal |
Volume | Issue | ISSN |
235 | 8 | 0377-0427 |
Citations | PageRank | References |
4 | 0.41 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dai-Qiang Chen | 1 | 92 | 8.35 |
| Lizhi Cheng | 2 | 290 | 34.84 |
| Su Fang | 3 | 61 | 5.73 |