为了实时地消除图像中的雾气,提出了一种基于暗原色先验理论的快速去雾算法。改进了透射率修复方法,显著地减少了算法的计算量;通过自适应调节透射率下限值和大气光成分值,扩大了去雾处理的适用范围;对复原的图像进行增强处理,改善了复原图像的整体视觉效果。实验结果表明,本文算法能有效地去除图像中的雾气,同时提高了算法的处理速度,有利于算法的实时实现。

In order to eliminate fog or haze in outdoor images in real time, a fast haze-removal algorithm is proposed based on the theory of dark channel prior. By improving the transmission repairing method, the computational effort is reduced. Furthermore, by self-adaptively controlling the values of transmission-rate lower limits and the global atmospheric lights, this algorithm could be used in more image dehazing applications. Finally, a post-processing procedure is adopted to enhance the visual effect of the dehazed image. Experiments show that the presented method processes the fog image effectively and fast,making the algorithm easy to achieve real-time capabilities.