Name
Abstract | ||
|---|---|---|
In this paper, we propose a new fast variational approach to dehaze and denoise simultaneously. The proposed method first estimates a transmission map using a windows adaptive method based on the celebrated dark channel prior. This transmission map can significantly reduce the edge artifact in the resulting image and enhance the estimation precision. The transmission map is then converted to a depth map, with which the new variational model can be built to seek the final haze-and noise-free image. The existence and uniqueness of a minimizer of the proposed variational model is further discussed. A numerical procedure based on the Chambolle-Pock algorithm is given, and the convergence of the algorithm is ensured. Extensive experimental results on real scenes demonstrate that our method can restore vivid and contrastive haze-and noise-free images effectively. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1137/130919696 | SIAM JOURNAL ON IMAGING SCIENCES |
Keywords | Field | DocType |
Chambolle-Pock algorithm,dehazing,denoising,variational method,weighted total variation | Convergence (routing),Noise reduction,Computer vision,Uniqueness,Mathematical optimization,Adaptive method,Variational method,Communication channel,Artificial intelligence,Depth map,Mathematics,Haze | Journal |
Volume | Issue | ISSN |
7 | 2 | 1936-4954 |
Citations | PageRank | References |
6 | 0.45 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Faming Fang | 1 | 6 | 0.45 |
| Fang Li | 2 | 187 | 9.99 |
| Tieyong Zeng | 3 | 17 | 0.92 |