QIU Xiang,DAI Ming,YIN Chuan-li.UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation[J].Optoelectronics Letters,2017,13(5):386-391 UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation Author Name Affiliation QIU Xiang  Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China  DAI Ming  Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China  YIN Chuan-li  Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China  Abstract:       Unmanned aerial vehicle (UAV) remote imaging is affected by the bad weather, and the obtained images have the disadvantages of low contrast, complex texture and blurring. In this paper, we propose a blind deconvolution model based on multiple scattering atmosphere point spread function (APSF) estimation to recovery the remote sensing image. According to Narasimhan analytical theory, a new multiple scattering restoration model is established based on the improved dichromatic model. Then using the L0 norm sparse priors of gradient and dark channel to estimate APSF blur kernel, the fast Fourier transform is used to recover the original clear image by Wiener filtering. By comparing with other state-of-the-art methods, the proposed method can correctly estimate blur kernel, effectively remove the atmospheric degradation phenomena, preserve image detail information and increase the quality evaluation indexes. Hits: 3935 Download times: 0 View Full Text    Download reader