IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE • 6 • SUMMER 2012 1939-1390/12/$31.00©2012IEEE PHOTO OF STREET: © COMSTOCK

Abstract–One source of accidents when driv-ing a vehicle is the presence of fog. Fog fades the colors and reduces the contrasts in the scene with respect to their distances from the driver. Vari-ous camera-based Advanced Driver Assistance Systems (ADAS) can be improved if efficient al-gorithms are designed for visibility enhancement in road images. The visibility enhancement algo-rithm proposed in [1] is not optimized for road images. In this paper, we reformulate the problem as the inference of the local atmospheric veil from constraints. The algorithm in [1] thus becomes a particular case. From this new derivation, we propose to better handle road images by introduc-ing an extra constraint taking into account that a large part of the image can be assumed to be a planar road. The advantages of the proposed local algorithm are the speed, the possibility to handle both color and gray-level images, and the small number of parameters. A new scheme is proposed for rating visibility enhancement algo-rithms based on the addition of several types of generated fog on synthetic and camera images. A comparative study and quantitative evaluation with other state-of-the-art algorithms is thus pro-posed. This evaluation demonstrates that the new algorithm produces better results with homoge-neous fog and that it is able to deal better with the presence of heterogeneous fog. Finally, we also propose a model allowing to evaluate the poten-tial safety benefit of an ADAS based on the display of defogged images. I