An adaptive factor-based method for improving dark channel prior dehazing
Hong Heather Yu, Chengtao Cai · 2016
The scattering effects of the atmospheric particles in the air affects significantly contrast reduction and color fading. To address this challenging, many attention have been paid to this issue. The foggy image generally contains the sky and non-sky regions while the pixel values in this two distinguished regions is different. The dark channel prior algorithm has been considered as one effective dehazing method which only uses one constant factor for the overall image regardless of the scene pattern. This imprudent procedure results in more darkness image color and fails to accomplish excellent results. In this paper we propose one adaptive factor-based approach to improving dark channel prior dehazing. In our methods, the foggy image is segmented into sky region and non-sky region by Otsu, the critical parameters i.e. light intensity and transmission ratio are obtained based on different factors. Some experiments have been conducted for validating dehazing performance of the proposed approach.