Name
Title | ||
|---|---|---|
Image deblurring with mixed regularization via the alternating direction method of multipliers |
Abstract | ||
|---|---|---|
In image deblurring problems, both local and nonlocal regularization priors are well studied. Local regularization prior assumes piecewise smoothness and transform-based sparsity, while the nonlocal one exploits self-similarity of images. We proposed a mixed regularization model which incorporates the advantages of both local adaptive sparsity prior and nonlocal sparsity prior resulting from the nonlocal self-similarity, and thus encourages a solution to simultaneously express both the local and nonlocal natures of images. The deblurring problem with mixed regularization can be transformed into a constrained optimization problem with separable structure via the variable splitting. Then this constrained optimization problem is solved by the alternating direction method of multipliers. Experimental results with a set of images under varying conditions demonstrate that the proposed method achieves the state-of-the-art deblurring performance. (C) 2015 SPIE and IS&T |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1117/1.JEI.24.4.043020 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
alternating direction method of multipliers,image deblurring,mixed regularization,variable splitting | Computer science,Matrix (mathematics),Separable space,Regularization (mathematics),Inverse problem,Artificial intelligence,Mathematical optimization,Deblurring,Pattern recognition,Piecewise smoothness,Algorithm,Constrained optimization problem,Prior probability | Journal |
Volume | Issue | ISSN |
24 | 4 | 1017-9909 |
Citations | PageRank | References |
0 | 0.34 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongyu Yin | 1 | 0 | 0.34 |
| Ganquan Wang | 2 | 0 | 0.34 |
| Bin Xu | 3 | 133 | 23.23 |
| Dingbo Kuang | 4 | 0 | 0.34 |