Name
Abstract | ||
|---|---|---|
Images obtained in poor weather circumstances such as fog, haze, smog, and thin cloud, suffer from severe contrast, texture, edge, and color degradation issues. To restore these weather degraded images, haze removal techniques are required. An efficient Gradient channel prior (GCP) is designed in this paper. It overcomes various issues such as texture distortion, transmission map misestimation, color distortion, and edge degradation. Thereafter, the transmission map is further refined using a guided L0 filter. Finally, the restoration model is also improved to reduce the over-saturation of pixels problem associated with the existing haze removal techniques. Extensive experimental results demonstrate that the proposed technique can significantly restore the hazy images, even if images contain high density of haze. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ins.2020.02.048 | Information Sciences |
Keywords | DocType | Volume |
Transmission map,Haze removal,Gradient channel prior,Guided L0 filter | Journal | 521 |
Issue | ISSN | Citations |
C | 0020-0255 | 2 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manjit Kaur | 1 | 23 | 8.41 |
| Dilbag Singh | 2 | 67 | 15.16 |
| Vijay Kumar | 3 | 229 | 21.59 |
| Kehui Sun | 4 | 86 | 14.71 |