Background: Capturing image in severe atmospheric catastrophe especially in fog critically degrades the quality of an image and thereby reduces its visibility of which in turn affects several computer vision applications like visual surveillance detection, intelligent vehicles, remote sensing, etc. Thus acquiring clear vision is the prime requirement of any image. In the last few years, many approaches have been directed towards solving this problem.
Methods: In this article, a comparative analysis has been made on different existing image defogging algorithms and then a technique has been proposed for image defogging based on dark channel prior strategy.
Results: Experimental results show that the proposed method shows efficient results by significantly improving the visual effects of images in foggy weather. Also the much higher computational time of the existing techniques has been reduced in this paper by using the proposed method.
Discussion: Qualitative assessment evaluation was performed on both benchmark and real time data sets for determining the efficacy of the technique used. Finally, the whole work is concluded with the relative advantages and shortcomings of the proposed technique.
Keywords: Visibility, dark channel prior, fast-guided filter, performance evaluation, image dehazing, color distortion.