Improvement of Dark Channel Prior via Image Denoising Techniques and Dehazing Algorithm

Abstract

When fog is present, the outstanding picture quality is drastically diminished, and there are a plethora of issues with video surveillance, tracking, and navigation. Therefore, several defogging procedures have been presented in the literature to eliminate it from an image. Multiple pictures or a single picture with special software can be used to de-fog a room. Multiple vision-based applications make extensive use of fog removal methods. It has been discovered that practically all the existing medical research neglects to address various issues, i.e. no approach is optimal in all situations. A novel strategy for clearing fog has been presented in this research. In this method, a CLAHE-based fully certainly fog eradication algorithm is combined with a trilateral filter and the Dark Channel Prior. The rule set has been developed and deployed in MATLAB. According to experimental results, the suggested set of rules outperforms earlier algorithms under certain assumptions.