| Abstract: |
Images captured in degraded weather conditions often suffer from bad visibility. Pre-existing haze removal methods, the ones that are effective are computationally complex too. In common de-hazing approaches, estimation of atmospheric light is not achieved properly as a consequence, haze is not removed significantly from the sky region. In this paper, an efficient method of haze removal from a single image is introduced. To restore haze-free images comprising of both sky as well as nonsky regions, we developed a linear model to predict atmospheric light and estimated the transmission map using the dark channel prior followed by an application of a guided filter for quick refinement. Several experiments were conducted on a large variety of images, both reference and nonreference, where the proposed image de-hazing algorithm outperforms most of the prevalent algorithms in terms of perceptual visibility of the scene and computational efficiency. The proposed method has been empirically measured through quantitative and qualitative evaluations while retaining structure, edges, and improved color. © 2021 World Scientific Publishing Company. |
