Name
Abstract | ||
|---|---|---|
Image deblurring problems appear frequently in astronomical image analysis. For image deblurring problems, it is reasonable to add a non-negativity constraint because of the physical meaning of the image. Previous research works are mainly full-space methods, i.e., solving a regularized optimization problem in a full space. To solve the problem more efficiently, we propose a subspace method. We first formulate the problem from full space to subspace and then use an interior-point trust-region method to solve it. The numerical experiments show that this method is suitable for ill-posed image deblurring problems. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.amc.2009.08.033 | Applied Mathematics and Computation |
Keywords | Field | DocType |
subspace,trust region,interior-point method,image deblurring,interior point,interior point method,image analysis,optimization problem | Trust region,Mathematical optimization,Subspace topology,Deblurring,Computational geometry,Numerical analysis,Interior point method,Optimization problem,Numerical linear algebra,Mathematics | Journal |
Volume | Issue | ISSN |
215 | 6 | Applied Mathematics and Computation |
Citations | PageRank | References |
3 | 0.69 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanfei Wang | 1 | 89 | 17.61 |
| Shiqian Ma | 2 | 1068 | 63.48 |