Name
Abstract | ||
|---|---|---|
In this paper, we study a fast total variation minimization method for image restoration. In the proposed method, we use the modified total variation minimization scheme to denoise the deblurred image. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show that the quality of restored images by the proposed method is competitive with those restored by the existing total variation restoration methods. We show the convergence of the alternating minimization algorithm and demonstrate that the algorithm is very efficient. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1137/070703533 | MULTISCALE MODELING & SIMULATION |
Keywords | Field | DocType |
image restoration,deblurring,denoising,total variation | Noise reduction,Convergence (routing),Mathematical optimization,Deblurring,Total variation denoising,Total variation minimization,Image restoration,Minimization algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
7 | 2 | 1540-3459 |
Citations | PageRank | References |
79 | 3.56 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu-Mei Huang | 1 | 258 | 11.83 |
| Ng Michael | 2 | 4231 | 311.70 |
| You-Wei Wen | 3 | 353 | 18.93 |