Single image dehazing using heterogeneous atmospheric light estimation

Abstract

Single image dehazing is a challenging problem because of its severely ill-posed nature. Single image dehazing mainly includes two important tasks, estimating the atmospheric light and calculating the medium transmission map. A single image dehazing algorithm using heterogeneous atmospheric light estimation is presented to enhance the quality of hazy images. First, a max-pooling-based strategy is developed to estimate the heterogeneous atmospheric light, which can accurately describe how the amount of scattering from one or multiple point light sources is spatial-variant. And then, an efficient adaptive filtering approach is introduced to refine the medium transmission map and suppress the annoying halo artifacts produced during the process of dehazing. Finally, based on the heterogeneous atmospheric scattering model, a photorealistic haze-free image can be recovered with the estimated atmospheric light and the refined medium transmission map. The experimental results on a variety of real-world images and synthetic hazy ones demonstrate that the addressed method outperforms state-of-the-art approaches through qualitative and quantitative metrics.