The presence of fog in the environment debases the nature of pictures caught by obvious camera sensors. The expulsion of dimness, called dehazing, is normally performed under the physical debasement demonstrate, which requires an answer of a not well presented opposite issue. Because of an awful climate like mist, rain, cloudiness and snow, the vision gets hindered. To alleviate the trouble of this issue, an idea earlier called dark channel prior (DCP) was as of late proposed and has gotten a lot of consideration. This paper proposes a novel and improved dehazing algorithm with dark channel prior (DCP) and the light channel where the latter is a sort of insights of fogged pictures. Besides, this guided channel is acquainted with refines of the dark channel and the light. To confirm the proposed calculation model and contrast it with DCP, a few precedents are given in this paper. The outcomes demonstrate that the calculation proposed is around 27 times quicker than the DCP which maintained a strategic distance from overall, and visual quality in the proposed display without an overhead issue is superior to that in the DCP. This additionally, empowers us to reveal clear and more powerful de-fogged images for each progression of the dehazing procedure. With these changes, the proposed technique might form the bases in video observation, smart transportation modules and remote detecting.

Keywords : Dark Channel Prior, Removal of Fog, Image Restore.