Towards Fog-Free In-Vehicle Vision Systems through Contrast Restoration

In foggy weather, the contrast of images grabbed by in-vehicle cameras in the visible light range is drastically degraded, which makes the current applications very sensitive to weather conditions. An onboard vision system should take fog effects into account. The effects of fog varies 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. Weather conditions are first estimated and then used to restore the contrast according to a scene structure which is inferred a priori and refined during the restoration process. Based on the aimed application, different algorithms with increasing complexities are proposed. Results are presented using sample road scenes under foggy weather and assessed by computing the contrast before and after restoration.