Name
Abstract | ||
|---|---|---|
We present a novel strategy to restore outdoor images degraded by the atmospheric phenomena such as haze or fog. Since both the depth map of the scene and the airlight constant are unknown, this problem is mathematically ill-posed. Firstly, we present a straightforward approach that is able to estimate accurately the airlight constant by searching the regions with the highest intensity. Afterwards, based on a graphical Markov random field (MRF) model, we introduce a robust optimization framework that is able to transport the local minima over large neighborhoods while smoothing the transmission map but also preserving the important depth discontinuities of the estimated depth. The method has been tested extensively for real outdoor images degraded by haze or fog. The comparative results with the existing state-of-the-art techniques demonstrate the advantage of our approach. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-23678-5_28 | CAIP (2) |
Keywords | Field | DocType |
estimated depth,single image restoration,important depth discontinuity,outdoor image,comparative result,outdoor scene,transmission map,straightforward approach,depth map,real outdoor image,atmospheric phenomenon,existing state-of-the-art technique | Unsharp masking,Computer vision,Pattern recognition,Markov random field,Robust optimization,Computer science,Maxima and minima,Smoothing,Artificial intelligence,Depth map,Image restoration,Haze | Conference |
Volume | ISSN | Citations |
6855 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Codruta Orniana Ancuti | 1 | 304 | 20.86 |
| Cosmin Ancuti | 2 | 314 | 22.39 |
| Philippe Bekaert | 3 | 758 | 67.00 |