Name
Abstract | ||
|---|---|---|
Haze is a common phenomenon in remote sensing images, which limits their applications. In this paper, a novel adaptive dehazing method is proposed for remote sensing images. First, a new prior, namely, dark channel-saturation prior, is developed based on the relation between dark channel and saturation of haze-free remote sensing images. Second, optimal transmission is estimated through the proposed prior on the basis of haze imaging model. Finally, using the estimated transmission, haze is removed from the images through the haze imaging model. Because no parameter needs to be set manually in this proposed method, the nonuniform haze can be adaptively removed. Experiments are carried out on simulated images and real images respectively. Compared with the other state-of-the-art methods, the proposed method can recover the scene in hazy regions more clearly along with better information retainability in haze-free regions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ACCESS.2018.2879893 | IEEE ACCESS |
Keywords | Field | DocType |
Adaptive dehazing,dark channel-saturation prior,haze removal,remote sensing | Histogram,Computer science,Remote sensing,Communication channel,Atmospheric model,Real image,Haze | Journal |
Volume | ISSN | Citations |
6 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fengying Xie | 1 | 182 | 15.33 |
| Jiajie Chen | 2 | 0 | 1.35 |
| Xiaoxi Pan | 3 | 1 | 0.69 |
| Zhiguo Jiang | 4 | 321 | 45.58 |