Fast Single Image Dehazing Using Morphological Reconstruction and Saturation Compensation

Despite having effective dehzing performance, single image dehazing methods based on the dark channel prior (DCP) still suffer from slightly dark dehazing results and oversaturated sky regions. An improved single image dehazing method, which combines image enhancement techniques with DCP model, is proposed to overcome this deficiency. Firstly, it is analyzed that the cause of darker results mainly lies in the air-light overestimation caused by bright ambient light and white objects. Then, the air-light estimation is modified by combining morphological reconstruction with DCP. Next, it is derived that appropriately increasing the saturation component can compensate for transmission underestimate, which can further alleviate the oversaturation. Finally, the image dehazed with modified air-light and transmission is further refined by linear intensity transformation to improve contrast. Extensive experiments validate the proposed method, which is on par with and even outperforms the state-of-the-art methods in subjective and objective evaluation.