Research On Haze Removal Algorithms For Digital Images

Images of outdoor scenes are usually degraded by the turbid medium (e.g., particles and water droplets) in the atmosphere. Haze, fog and smoke are such phenomena due to atmospheric absorption and scattering. Images of outdoor scenes lose visiblity and contrast due to the presence of atmospheric haze, fog and smoke. Haze removal can significantly increase the visiblity of the scene and correct the color shift caused by the airlight.We introduced the widely used haze removal methods and make comparative analysis on them. Generally, there are two kinds of haze removal methods:one is relible to additional information and the other is only related to the given hazy image. Since the former one relys on much additional information, it is not pratical in most situations. The recently proposed dark channel prior-based approach can be categorized to the latter one which appears to be the most successful solution and produces the best result in most cases. However, this approach suffers from a complex depth map refinement process, which consumes much computational time.In this paper, we propose a novel fast depth map approximation method using the dark channel prior. This approximation makes use of the pixel-wise depth map and the observation that most dehazing artifacts occur in the area in which the original estimated depth map has large difference from its pixel-wise depth map. For fast implementation, we simply replace these edge area depth information by the newly estimated depth information. Experiments show that comparing with the original dark channel approach, the proposed new method has a speedup gain of about28or more while at the same time produces similar or better results.