Name
Abstract | ||
|---|---|---|
In adverse weather conditions, in particular, in daylight fog, the contrast of images grabbed by in-vehicle cameras in the visible light range is drastically degraded, which makes current driver assistance that relies on cameras very sensitive to weather conditions. An onboard vision system should take weather effects into account. The effects of daylight fog vary across the scene and are exponential with respect to the depth of scene points. Because it is not possible in this context to compute the road scene structure beforehand, contrary to fixed camera surveillance, a new scheme is proposed. Fog density is first estimated and then used to restore the contrast using a flat-world assumption on the segmented free space in front of a moving vehicle. A scene structure is estimated and used to refine the restoration process. Results are presented using sample road scenes under foggy weather and assessed by computing the visibility level enhancement that is gained by the method. Finally, we show applications to the enhancement in daylight fog of low-level algorithms that are used in advanced camera-based driver assistance. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TITS.2010.2046165 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
climate mitigation,computer vision,daylighting,driver information systems,fog,image enhancement,image restoration,video surveillance,visibility,weather forecasting,adverse weather conditions,camera surveillance,contrast restoration,daylight fog,driver assistance,in-vehicle cameras,onboard vision system,visibility level enhancement,visibility loss,weather mitigation,Advanced driver-assistance systems,contrast restoration,fog removal,real-time image processing | Computer vision,Visibility,Machine vision,Simulation,Daylight,Distance fog,Advanced driver assistance systems,Artificial intelligence,Engineering,Image restoration,Weather forecasting,Daylighting | Journal |
Volume | Issue | ISSN |
11 | 2 | 1524-9050 |
Citations | PageRank | References |
21 | 1.10 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Hautiére | 1 | 572 | 28.07 |
| Jean-Philippe Tarel | 2 | 805 | 56.63 |
| Didier Aubert | 3 | 361 | 35.97 |