Sky detection‐ and texture smoothing‐based high‐visibility haze removal from images and videos

Abstract To address the gloomy sky and the low contrast caused by the left fog in the existing image dehazing methods, we propose a robust haze removal algorithm for images and videos. First, a sky detection‐based adaptive atmospheric light estimation method is designed for brighter and cleaner restoration results for the sky regions. Second, in order to reconstruct a transmission map in line with the depth variation, we preprocess the input image with texture smoothing to keep the color consistency inside the same planar object and devise a texture smoothing‐based robust transmission estimation method, with which the contrast and color saturation of fog‐free image are greatly promoted. Finally, the restored results are post‐processed with the joint bilateral filter for the purpose of noise removal. What's more, a guided filter‐based temporally coherent atmospheric light smoothing strategy and a Gaussian filter‐based spatial‐temporally coherent transmission smoothing strategy are put forward for video dehazing, which can ensure the spatial as well as temporal continuity of the haze‐free videos. Experimental results show that the recovered haze‐free images and videos have high contrast and color saturation with cleaner sky regions, and the haze‐free videos are free of jittering and flickering phenomena.