Image Dehazing Algorithm for Relieving Halo Effect and Color Distortion in Smooth Regions

Abstract

Aiming to solve the problem that the dehazing algorithm based on the dark channel produces halo effect and color distortion in smooth region, a novel dehazing algorithm is proposed using bilateral filter guided homomorphic filtering. Firstly, a nonlinear stretch model is constructed to characterize the contrast relationship among each color component before and after dehazing. The model is proportional to the difference between the original pixels and the atmospheric light value while inversely proportional to the transmittance. Secondly, the coarse transmittance map is decomposed into an atmospheric light component and a reflection component by use of the bilateral filter guided spatial homomorphic filtering. Finally, an adaptive function is defined, taking the ratio of the foreground area as a variable. It is used to calculate a refined transmittance map by linearly weighting the atmospheric light component and the reflection component, and then employed to accomplish the dehazing with the dark channel prior model. The real foggy images in O-HAZE and RESIDE datasets is used as the test data, and the UCIQE, FADE, SSIM, NIQE, and hue restoration ability are adopted as the objective evaluation matrics. The evaluation scores of the proposed algorithm increase by 21.68% on average, compared with those of the state-of-art algorithms. The results show that the proposed algorithm is able to effectively avoid the color distortion in large smooth area, as well as the halo & fake edge effects at the edges and contours, achieves higher subjective and objective quality.