Quick Shift Segmentation Guided Single Image Haze Removal Algorithm

This paper presents a novel image haze removal approach from single image. In the algorithm, the constant albedo and dark channel prior methods are combined to represent the transmission model of hazed image. And then, the quick shift segmentation approach is introduced to decompose the input image into some gray level consistent areas. Compared with traditional fixed image partition schemes, better estimation of the atmospheric light can be obtained as well as to avoid the problem of halo artifacts. With the improved haze image modeling approach and atmospheric light estimation, the dehazed image with better visual quality can be achieved.