Efficient Image Dehazing with Boundary Constraint and Contextual Regularization

Gaofeng Meng, Ying Wang, Jiangyong Duan, Shiming Xiang, Chunhong Pan; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2013, pp. 617-624

suffer from bad visibility. In this paper, we propose an efficient regularization method to remove hazes from a single input image. Our method benefits much from an exploration on the inherent boundary constraint on the transmission function. This constraint, combined with a weighted ms1 sonffnbased contextual regularization, is modeled into an optimization problem to estimate the unknown scene transmission. A quite efficient algorithm based on variable splitting is also presented to solve the problem. The proposed method requires only a few general assumptions and can restore a high-quality haze-free image with faithful colors and fine image details. Experimental results on a variety of haze images demonstrate the effectiveness and efficiency of the proposed method. Keywords-image processing; single image dehazing; visibility enhancement; I. I NTRODUCTION When one takes a picture in foggy weather conditions, the obtained image often suffers from poor visibility. The distant objects in the fog lose the contrasts and get blurred with