Name
Abstract | ||
|---|---|---|
Existing learning-based atmospheric particle-removal approaches such as those used for rainy and hazy images are designed with strong assumptions regarding spatial frequency, trajectory, and translucency. However, the removal of snow particles is more complicated because they possess additional attributes of particle size and shape, and these attributes may vary within a single image. Currently, h... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIP.2018.2806202 | IEEE Transactions on Image Processing |
Keywords | DocType | Volume |
Snow,Rain,Feature extraction,Image color analysis,Shape,Atmospheric modeling,Image restoration | Journal | 27 |
Issue | ISSN | Citations |
6 | 1057-7149 | 10 |
PageRank | References | Authors |
0.55 | 29 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yun-Fu Liu | 1 | 277 | 19.65 |
| Da-Wei Jaw | 2 | 10 | 0.55 |
| Shih-Chia Huang | 3 | 43 | 5.99 |
| Jenq-Neng Hwang | 4 | 1675 | 206.57 |