《[2016_PAMI]_Single_Image_Haze_Removal_Using_Dark_Channel_Prior》.pdf

《[2016_PAMI]_Single_Image_Haze_Removal_Using_Dark_Channel_Prior》.pdf

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《[2016_PAMI]_Single_Image_Haze_Removal_Using_Dark_Channel_Prior》.pdf

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 33, NO. 12, DECEMBER 2011 2341 Single Image Haze Removal Using Dark Channel Prior Kaiming He, Jian Sun, and Xiaoou Tang, Fellow, IEEE Abstract—In this paper, we propose a simple but effective image prior—dark channel prior to remove haze from a single input image. The dark channel prior is a kind of statistics of outdoor haze-free images. It is based on a key observation—most local patches in outdoor haze-free images contain some pixels whose intensity is very low in at least one color channel. Using this prior with the haze imaging model, we can directly estimate the thickness of the haze and recover a high-quality haze-free image. Results on a variety of hazy images demonstrate the power of the proposed prior. Moreover, a high-quality depth map can also be obtained as a byproduct of haze removal. Index Terms—Dehaze, defog, image restoration, depth estimation. Ç 1 INTRODUCTION MAGES of outdoor scenes are usually degraded by the editing. Haze or fog can be a useful depth clue for scene Iturbid medium (e.g., particles and water droplets) in understanding. A bad hazy image can be put to good use. the atmosphere. Haze, fog, and smoke are such phenomena However, haze removal is a challenging problem because due to atmospheric absorption and scattering. The irradiance the haze is dependent on the unknown depth. The problem is received by the camera from the scene point is attenuated underconstrained if the input is only a single hazy image. along the line of sight. Furthermore, the incomi

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