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静态计算光谱成像仪图谱反演的关键数据处理技术
引用本文:刘扬阳,吕群波,曾晓茹,黄旻,相里斌. 静态计算光谱成像仪图谱反演的关键数据处理技术[J]. 物理学报, 2013, 62(6): 60203-060203. DOI: 10.7498/aps.62.060203
作者姓名:刘扬阳  吕群波  曾晓茹  黄旻  相里斌
作者单位:中国科学院光电研究院, 计算光学成像技术重点实验室, 北京 100094
基金项目:国家高技术研究发展计划(批准号: 2011AA7012022)资助的课题.
摘    要:静态计算光谱成像技术中图谱反演环节是实现其理论优势极为关键的一步, 是决定最终获得图谱质量优劣的数据处理技术. 本文为此专注于计算光谱的图谱反演环节,对图像压缩感知理论算法、图像重构算法、 以及针对图谱三维数据的反演算法都开展了深入的研究和比较, 并结合所研制系统的图谱数据传输全链路和工程研制过程中误差等因素进行全面详尽的仿真验证, 给出各种图谱反演算法验证、分析结果. 指出静态计算光谱成像系统研制中图谱反演环节的关键数据处理问题,适合采用的算法及其优化路线. 为顺利研制静态计算光谱成像仪,保证其理论优势的实现,提供了详实的分析、参考依据.关键词:计算光谱编码孔径压缩感知图谱反演

关 键 词:计算光谱  编码孔径  压缩感知  图谱反演
收稿时间:2012-06-26

Critical data processing technology for spectral image inversion in a static computational spectral imager
Liu Yang-Yang,L,uuml,Qun-Bo,Zeng Xiao-Ru,Huang Min,Xiang Li-Bin. Critical data processing technology for spectral image inversion in a static computational spectral imager[J]. Acta Physica Sinica, 2013, 62(6): 60203-060203. DOI: 10.7498/aps.62.060203
Authors:Liu Yang-Yang    Qun-Bo  Zeng Xiao-Ru  Huang Min  Xiang Li-Bin
Affiliation:Academy of Opto-electronics, Chinese Academy of Sciences, Key Laboratory of Computational Optics Imaging Technology, Beijing 100094, China
Abstract:To carry out spectral image inversion in a static computational spectral imager is a crucial step for accomplishing its theoretical advantages, so the data processing technology for spectral image inversion will determine the final spectral image achieved. Focusing on the spectral image inversion, we have investigated various algorithms such as image reconstruction, image compressed sensing and spectral image inversion theories, and compared them carefully. By taking into account the data transmission link of the system and the error in the engineering development process, a comprehensive simulation is carried out. The key issue of spectral image inversion, and also how to use the inversion algorithms to achieve its optimized routes are pointed out. So a detailed analysis for realizing the theoretical advantages and ensuring instrument technology development is provided.
Keywords:computational spectral  code aperture  compressed sensing  spectral image inversion
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