Recovering of images degraded by atmosphere

Remote sensing images are seriously degraded by multiple scattering and bad weather. Through the analysis of the radiative transfer procedure in atmosphere, an image atmospheric degradation model considering the influence of atmospheric absorption multiple scattering and non-uniform distribution is proposed in this paper. Based on the proposed model, a novel recovering method is presented to eliminate atmospheric degradation. Mean-shift image segmentation and block-wise deconvolution are used to reduce time cost, retaining a good result. The recovering results indicate that the proposed method can significantly remove atmospheric degradation and effectively improve contrast compared with other removal methods. The results also illustrate that our method is suitable for various degraded remote sensing, including images with large field of view (FOV), images taken in side-glance situations, image degraded by atmospheric non-uniform distribution and images with various forms of clouds.