Image dehazing using window-based integrated means filter

Image acquisition is generally susceptible to poor environmental conditions such as fog, smog, haze, etc. However, designing an efficient image dehazing technique is still an ill posed problem. Extensive review of the competitive haze removal approaches reveal that the texture preservation and computational speed are still a challenging issues. Therefore, in this paper, initially, a mask is utilized to decompose an input image into low and high frequency regions based on image gradient magnitude. Thereafter, a Gradient sensitive loss (GSL) is designed to obtain the depth information from an input hazy image. Thereafter, transmission map is refined by designing an efficient filter named as Window-based integrated means filter (WIMF). Finally, the restoration model is utilized to recover the hazy images. Experimental analysis reveals that the proposed dehazing technique achieves considerable results beyond the prototypes of the benchmarks. Additionally, the proposed technique outperforms the state-of-the-arts in single image dehazing approaches.