Name
Abstract | ||
|---|---|---|
Since no temporal information can be exploited, rain and snow removal from single image is a challenging problem. In this paper, an improved rain and snow removal method from single image is proposed by designing a guided L0 smoothing filter. The designed filter is inspired by the previous L0 gradient minimization. Then a coarse rain-free or snow-free image can be obtained with the proposed filter, and the final refined result is recovered by a further minimization operation depending on the observed image. Experimental results show that the proposed algorithm generates better or comparable outputs than the state-of-the-art algorithms in rain and snow removal task for single image. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s11042-015-2657-7 | Multimedia Tools and Applications |
Keywords | Field | DocType |
Single image rain and snow removal,Guided filter,L0 gradient minimization,Guided L0 smoothing filter | Computer vision,Computer science,Smoothing filter,Rain and snow mixed,Minification,Artificial intelligence,Edge-preserving smoothing | Journal |
Volume | Issue | ISSN |
75 | 5 | 1380-7501 |
Citations | PageRank | References |
8 | 0.45 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinghao Ding | 1 | 591 | 52.95 |
| Liqin Chen | 2 | 10 | 0.81 |
| xianhui zheng | 3 | 8 | 0.45 |
| Yue Huang | 4 | 317 | 29.82 |
| Delu Zeng | 5 | 164 | 11.46 |