Name
Abstract | ||
|---|---|---|
Driver assistance systems based on camera are strongly disturbed by the presence of foggy weather. The restoration of images, as pre-processing, would improve the performances of such systems. In this paper, we propose a method to restore the image contrast of foggy road scenes combining a physical approach, based on Koschmieders model and a signals approach, based on local histogram equalization. Then we optimize the parameters of our method using a simulated annealing. This method, evaluated on a reference image database, presents a significant improvement compared to other methods and gives consistent results for both homogeneous and inhomogeneous fog. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICCVW.2011.6130501 | ICCV Workshops |
Keywords | Field | DocType |
inhomogeneous fog,reference image database,road images,foggy weather,camera,local histogram equalization,image restoration,image contrast,cameras,foggy road scenes,contrast restoration,driver information systems,road traffic,driver assistance systems,simulated annealing,signals approach,koschmieders model,histogram equalization,histograms,sensitivity,mathematical model | Simulated annealing,Computer vision,Histogram,Pattern recognition,Computer science,Homogeneous,Reference image,Advanced driver assistance systems,Road traffic,Artificial intelligence,Image restoration,Histogram equalization | Conference |
Volume | Issue | ISBN |
2011 | 1 | 978-1-4673-0062-9 |
Citations | PageRank | References |
1 | 0.36 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Houssam Halmaoui | 1 | 106 | 4.90 |
| Aurélien Cord | 2 | 166 | 9.84 |
| Nicolas Hautiére | 3 | 572 | 28.07 |