Single image dehazing using a novel criterion based segmenting dark channel prior
Chao Zhang, Yanjun Zhang, Jihua Lu · 2020
Single image dehazing has become a hot issue in image processing. Almost all the dehazing algorithms suffer from two problems: bringing out the halo artifacts or high computational complexity. In this paper, we propose a novel single image dehazing algorithm with a modified criterion based segmenting dark channel prior (SDCP), which is simple and effective. Based on the estimated global atmospheric light, the transmission map (TM) is obtained by a novel region segmenting logic. Then, the TM is smoothed by guided image filtering (GF) with the edge information being preserved. Experiments reveal that the proposed algorithm eliminates the halo artifacts more effectively than SDCP or GF based dark channel prior (DCP) both subjectively and objectively. Also, it is faster than the soft matting based DCP.