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高分辨大视场紫外-可见光偏振成像融合处理技术 被引量:6

Ultraviolet-Visible Polarimetric Imaging and Image Fusion Technology with High Resolution and Large Field-of-View
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摘要 采用蒙特卡罗方法对水云下大气的偏振态分布进行了仿真分析,所建立的水云大气环境在紫外360~400 nm波段的偏振度响应最大。采用紫外-可见光偏振成像技术对同一视场下的楼房、云和天空进行了偏振成像实验,并用霍夫变换分割方法对图像中的每个区域进行了统计分析,发现观测区域内无云区与云区的偏振角均值相对差为1.6%,偏振度均值相对差为-14%,证明了大气偏振角较偏振度稳健。紫外光和可见光在对云目标的偏振观测中存在互补性,采用拉普拉斯金字塔图像融合技术能够提高对大气目标的探测能力,验证了大视场高分辨紫外-可见光偏振成像技术在大气探测中的可行性和有效性。 The Monte Carlo method is used to simulate the atmospheric polarimetric distribution under water clouds. The results show that the polarimetric response of water clouds in the ultraviolet(UV) band of 360-400 nm is the largest as compared to that of other spectra. Polarization pictures of buildings, clouds, and the sky in the same field of view are taken using UV-visible polarimetric imaging technology. Hough transform is used to divide these pictures, and statistical analysis is applied to each segment. The statistical results show that the relative differences of the polarization degree and polarization angle of the cloud-free and cloudy areas are-14% and 1.6%, respectively, providing the robustness of polarization angle in atmospheric detection. The UV and visible are found to be complementary in polarimetric detection for the clouds. Thus, image fusion technology in conjunction with a Laplacian pyramid can improve the detection capability for atmospheric targets. Results verify that the UV-visible polarimetric imaging technology with large field-of-view and high resolution is feasible and effective for atmospheric detection.
作者 李清灵 尹达一 庾金涛 李磊 Li Qingling;Yin Dayi;Yujintao;Li Lei(University of Chinese Academy of Sciences,Beijing 100049,China;Shanghai Institute of Technical Physics t Chinese Academy of Sciences,Shanghai 200083,China;Key Laboratory of Infrared System Detection and Imaging Technology,Chinese Academy of Sciences,Shanghai 200083,China)
出处 《光学学报》 EI CAS CSCD 北大核心 2019年第6期119-126,共8页 Acta Optica Sinica
基金 国家自然科学基金(40776100)
关键词 成像系统 偏振成像 高分辨 大视场 紫外-可见光 融合处理 imaging systems polarimetric imaging high resolution large field of view ultraviolet-visible image fusion
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