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UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation
Qiu, X.; M. Dai and C.-l. Yin
2017
Source PublicationOptoelectronics Letters
Volume13Issue:5
AbstractUnmanned 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. 2017, Tianjin University of Technology and Springer-Verlag GmbH Germany.
Indexed Bysci ; ei
Language英语
Document Type期刊论文
Identifierhttp://ir.ciomp.ac.cn/handle/181722/59165
Collection中科院长春光机所知识产出
Recommended Citation
GB/T 7714
Qiu, X.,M. Dai and C.-l. Yin. UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation[J]. Optoelectronics Letters,2017,13(5).
APA Qiu, X.,&M. Dai and C.-l. Yin.(2017).UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation.Optoelectronics Letters,13(5).
MLA Qiu, X.,et al."UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation".Optoelectronics Letters 13.5(2017).
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