Fog Removal Algorithm Using Anisotropic Diffusion And Histogram Stretching
M. Sailaja · Journal of Emerging Technologies and Innovative Research · 2017
Poor climate conditions which includes fog, mist, haze degrades atmospheric visibility. Image quality and efficiency of the computer vision algorithms like surveillance and object tracking degrades because of Low visibility.Thus, it's more critical to make vision algorithms more strong to the change in climate situations. Low visibility in poor climate is due to the suspension of water particles in surroundings .Light coming from the atmosphere and mild contemplated from an object are scattered by those water particles, resulting the low visibility of the scene. Fog removal algorithm is used to put off the fog from the foggy photograph/scene. The Existing Dark channel prior eliminates fog based on dark channel. But this technique fails when scene objects are similar to sky i.e. for sky image. In order to over this trouble we cross for Anisotropic diffusion algorithm. Anisotropic Diffusion algorithm eliminates the fog from photograph and produces an image having better visibility as compared to existing techniques. This algorithm contains many steps like anisotropic diffusion, contrast enhancement and denoising. Proposed algorithm is independent of amount fog. The proposed method also applicable for gray scale images.Along with the RGB (red, blue and green) colour version, proposed algorithm can work for HSI version which further reduces the computation. Proposed algorithm has a huge application in tracking and navigation.