Vision enhancement through single image fog removal

Contrast and color of the captured pictures are degraded under foggy weather conditions and this degradation is often attributed to attenuation and airlight. To reduce the number of road accidents through vision enhancement in turbid weather, an efficient fog removal technique plays a vital role as fog greatly reduces the visibility and hence affects the computer vision algorithms such as surveillance, tracking and Fog Vision Enhancement System (FVES). In this paper, a novel and effective algorithm is proposed for single image fog removal that's capable of handling images of gray and color channels. The proposed algorithm introduces Dark Channel Prior (DCP) followed by Weighted Least Square (WLS) and High Dynamic Range (HDR) based fog removal scheme. The qualitative and quantitative analysis is applied for the assessment of defogged images obtained from the proposed methodology and is additionally compared with the different fog removal algorithms to establish its superiority. The foremost dominant advantage of the proposed algorithm is its capability to preserve sharp details whereas maintaining the color quality.