An Efficient Image Haze Removal Algorithm Based On New Accurate Depth And Light Estimation Algorithm

Single image Dehazing has become a challenging task for a variety of image processing and computer applications. Many attempts have been devised to recover faded colors and improve image contrast. Such methods, however, do not achieve maximum restoration, as images are often subject to color distortion. This paper proposes an efficient single image Dehazing algorithm that offers satisfactory scene radiance restoration. The proposed method stands on the estimation of two key indices; image blur and atmospheric light that can be employed in the Image Formation Model (IFM) to recover scene radiance of the hazy image. More clearly, we propose an efficient depth estimation method using image blur. Most existing algorithms implement atmospheric light as a constant which often leads to inaccurate estimations, we propose a new algorithm "A-Estimate" based on blur and energy to estimate the atmospheric light accurately, an adaptive transmission map also has been proposed. Experimental results on real and synthesized hazy images demonstrate an improved performance in the proposed method when compared to existing state-of-the-art methods.