Name
Abstract | ||
|---|---|---|
In this paper, we consider and study a total variation minimization model for color image restoration. In the proposed model, we use the color total variation minimization scheme to denoise the deblurred color image. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. We show the convergence of the alternating minimization algorithm and demonstrate that the algorithm is very efficient. Our experimental results show that the quality of restored color images by the proposed method are competitive with the other tested methods. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TIP.2008.2003406 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
deblurred color image,color image restoration,total variation minimization model,color total variation minimization,color image,proposed total variation minimization,minimization algorithm,efficient total variation minimization,minimisation,total variation,color,algorithm design and analysis,image restoration,denoising,convergence,test methods,minimization | Noise reduction,Computer vision,Algorithm design,Pattern recognition,Deblurring,Image processing,Minimisation (psychology),Minification,Artificial intelligence,Image restoration,Mathematics,Color image | Journal |
Volume | Issue | ISSN |
17 | 11 | 1057-7149 |
Citations | PageRank | References |
23 | 0.86 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| You-Wei Wen | 1 | 353 | 18.93 |
| Ng Michael | 2 | 4231 | 311.70 |
| Yu-Mei Huang | 3 | 258 | 11.83 |