A multi-scale fusion-based dark channel prior dehazing algorithm
Yujun Zeng, Xiaolin Liu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
During model-based image dehazing, the role of the accuracy of transmission estimation is crucial, which has a decisive effect on the final result. Considering that an ideal transmission map must be smooth, edge-preserving and free of redundant false details, a fusion-based dark channel prior (DCP) dehazing algorithm is presented in this paper. On the basis of DCP, a pixel-wise and a patch-wise transmission maps are obtained. Then an L0 smoothing filter and a large scale Gaussian filter are applied to them respectively. Finally, a much more accurate refined transmission map is attained through fusion and a haze-free image is restored using the atmosphere degradation model. Furthermore, a novel scheme for setting the lower bound of transmission adaptively is also put forward. Experiments demonstrate a better and faster dehazing capability over original DCP algorithm and state-of-the-art dehazing methods, especially in suppressing halo artifacts, restoring details and coping with the haze existing in small-scale areas of depth discontinuity occluded by foreground..