Single image dehazing by latent region-segmentation based transmission estimation and weighted L 1-norm regularisation

Image dehazing is a useful technique which can eliminate the bad effect of haze on images and enhance the performances of image/video processing algorithms in the hazy weather. In this study, a single image dehazing method is proposed. The authors estimate the initial transmission properly based on latent region-segmentation and refine the estimated initial transmission by an objective function with a novel weighted L1-norm regularisation term. The half-quadratic splitting minimisation method is employed to solve this optimisation problem. They also define an evaluation function to estimate the reliable global atmospheric light. With the refined transmission map and atmospheric light they recover the haze-free image by the haze imaging model. The authors’ method is compared with three state-of-the-art methods and is also validated by two image quality assessment methods. The comparative experimental results and evaluations demonstrate that their method can recover comparable and even better results with clear details, low contrast loss and high contrast in most cases.