Visibility enhancement of images degraded by hazy weather conditions using modified non-local approach

Natural images captured under bad weather situations suffer from poor visibility and contrast problems. Object tracking and recognition under hazy bad weather conditions is a very difficult task for real time applications. Therefore, in this paper, we have proposed an efficient dehazy algorithm for visibility and contrast enhancement of color hazy images. The proposed algorithm works in two phases. In the first phase, a non local approach is applied in the hazy model, which is a pixel based approach not a patch based. Pixels are spread over the entire image plane and positioned at different distance from the sensor, so this approach is called non local. Degradation is different for every pixel therefore; estimation of the transmission map for every pixel through the haze line is the essential step. After the first phase, the image becomes unnatural and dimmed, therefore to proper tone mapping and improving the visual quality of the image, we applied the S-shaped mapping function in the second phase. The quantitative results of the proposed algorithm and other existing dehazy algorithms for color hazy images are obtained in terms of Hazy Reduction factor(HRF), and measure of enhancement factor(EMF) on different hazy image databases. Qualitative results reveal that the visual quality of the proposed algorithm is better than other existing de-hazy algorithms. Simulation results demonstrate that the proposed algorithm provides better results as compared to other existing dehazy algorithms for color hazy images. Proposed algorithm is highly efficient as compare to other latest dehazy algorithms.