Single image fog and haze removal based on self-adaptive guided image filter and color channel information of sky region

In this paper, we report an effective algorithm for removing both fog and haze from a single image. Existing algorithms based on atmospheric degeneration model generally lead to non-definite solutions for the haze and thick fog images, though they are very efficient for thin fog images. In general, as the algorithms based on vision enhancement cannot automatically adjust weight coefficient for the different structure images, the excessive or inadequate enhancement may emerge. In this paper an original degradation image is primarily segmented into the sky and non-sky regions, and then the main boundaries of non-sky region are extracted using L0 smoothing filter. So our vision enhancement algorithm automatically adjusts weight coefficient according to various structure images. At the stage of vision enhancement, guided image filter famous for its excellent boundary preservation is adopted. As for haze image, the color channel information scattered by haze particles can be obtained in the sky region to make an effective color correction. Both the subjective and objective evaluations of experimental results demonstrate that the proposed algorithm has more outstanding recovery effect for haze and thick fog images. Moreover, the proposed algorithm can judge fog or haze image, which is a by-product of this research.