An Adaptive Combination of Dark and Bright Channel Priors for Single Image Dehazing

摘要

Dehazing methods based on prior assumptions derivedrnfrom statistical image properties fail when these properties dornnot hold. This is most likely to happen when the scene containsrnlarge bright areas, such as snow and sky, due to the ambiguityrnbetween the airlight and the depth information. This is the casernfor the popular dehazing method Dark Channel Prior. In order tornimprove its performance, the authors propose to combine it with thernrecent multiscale STRESS, which serves to estimate Bright ChannelrnPrior. Visual and quantitative evaluations show that this methodrnoutperforms Dark Channel Prior and competes with the most robustrndehazing methods, since it separates bright and dark areas andrntherefore reduces the color cast in very bright regions.