Dehazing with improved heterogeneous atmosphere light estimation and a nonlinear color attenuation prior model
Sheng Zhang, Chunmei Qing, Xiangmin Xu, Jianxiu Jin, Huiping Qin · 2016
In this paper, we propose an improved heterogeneous atmosphere light estimation method and a novel depth estimation algorithm with Color Attenuation Prior (CAP) to dehaze single image. Firstly, it estimates the atmosphere light with mean-pooling on the illuminance component from HSV color space. The estimated atmosphere light is more robust because of its independence of a specified pixel. Secondly, the scene depth is estimated by a nonlinear CAP model which can overcome the defects of the occurrence of negative scene depths from the linear CAP model. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art methods in dehazing images.