Name
Abstract | ||
|---|---|---|
Due to the fast inference and good performance, discriminative learning methods have been widely studied in image denoising. However, these methods mostly learn a specific model for each noise level, and require multiple models for denoising images with different noise levels. They also lack flexibility to deal with spatially variant noise, limiting their applications in practical denoising. To ad... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TIP.2018.2839891 | IEEE Transactions on Image Processing |
Keywords | DocType | Volume |
Noise reduction,Noise level,Image denoising,Noise measurement,Learning systems,AWGN,Visualization | Journal | 27 |
Issue | ISSN | Citations |
9 | 1057-7149 | 72 |
PageRank | References | Authors |
1.76 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai Zhang | 1 | 686 | 26.59 |
| Wangmeng Zuo | 2 | 3833 | 173.11 |
| Lei Zhang | 3 | 16326 | 543.99 |