A Novel Localized Approach to Single Image Dehazing Based on Haze-Lines

Abstract

Haze is a common atmospheric degradation which reduces the visibility of outdoor images by creating a thin veil over the scene. Removal of haze from a natural scene is a complex process because of the difficulty in getting any prior information other than the hazy image. In natural images, the assumption of global atmospheric light may not be true because of the non uniform nature of haze. Most of the state-of-the-art methods use a patch based algorithm for the estimation of global atmospheric light and transmission map. In this work, we propose a patch based dehazing technique which estimates localized atmospheric light by clustering the minimum channel of the image using Self Organizing Map (SOM). This local atmospheric light is used in haze-line based dehazing method for the estimation of transmission map. It gives a better estimate of haze content compared to the existing methods and results in better dehazing. The pixel based haze-line model has reduced complexity when compared to dark channel prior based methods. This excludes the requirement of any transmission map refinement operations which makes the algorithm simpler and faster.