Name
Abstract | ||
|---|---|---|
In this paper, we study the restoration of blurred images corrupted by impulse noise or mixed impulse plus Gaussian noises. In the proposed method, we use the modified total variation minimization scheme to regularize the deblurred image and fill in suitable values for noisy image pixels where these are detected by median-type filters. An alternating minimization algorithm is employed to solve the proposed total variation minimization problem. Our experimental results show the proposed algorithm is very efficient and the quality of restored images by the proposed method is competitive with those restored by the existing variational image restoration methods. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/LSP.2009.2016835 | IEEE Signal Process. Lett. |
Keywords | Field | DocType |
median filters,deblurring,deblurred image,impulse noise,image restoration,total variation,image restoration method,denoising,minimization algorithm,gaussian noise,minimisation,median-type filter,mathematics,white noise,tv,pixel,degradation | Noise reduction,Computer vision,Mathematical optimization,Deblurring,Impulse (physics),Gaussian,Pixel,Artificial intelligence,Impulse noise,Image restoration,Gaussian noise,Mathematics | Journal |
Volume | Issue | ISSN |
16 | 6 | 1070-9908 |
Citations | PageRank | References |
23 | 0.74 | 15 |
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 |