北京航空航天大学学报 ›› 2018, Vol. 44 ›› Issue (12): 2463-2469.doi: 10.13700/j.bh.1001-5965.2018.0376

• 信息与电子技术 • 上一篇    下一篇

基于软件定义微纳卫星的多模式计算光学成像技术

刘扬阳1,2, 吕群波1,2, 谭政1, 裴琳琳1, 李伟艳1, 王建威1   

  1. 1. 中国科学院光电研究院 中国科学院计算光学成像技术重点实验室, 北京 100094;
    2. 中国科学院大学 光电学院, 北京 100049
  • 收稿日期:2018-06-20 修回日期:2018-07-27 出版日期:2018-12-20 发布日期:2018-12-28
  • 通讯作者: 吕群波 E-mail:lvqunbo@aoe.ac.cn
  • 作者简介:刘扬阳,女,博士,研究员,博士生导师。主要研究方向:光谱成像、光学成像、图像理解;吕群波,男,博士,研究员,博士生导师。主要研究方向:光谱成像、光学成像、图像理解。

Multi-mode computational optical imaging technology based on software-defined micro-nano satellite

LIU Yangyang1,2, LYU Qunbo1,2, TAN Zheng1, PEI Linlin1, LI Weiyan1, WANG Jianwei1   

  1. 1. Key Laboratory of Computational Optical Imaging Technology of the Chinese Academy of Sciences, Academy of Opto-electronics, Chinese Academy of Sciences, Beijing 100094, China;
    2. School of Opto-eletronics, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-06-20 Revised:2018-07-27 Online:2018-12-20 Published:2018-12-28

摘要: 为实现有效载荷具备上载软件在轨定义多功能、软件可控多功能、参数可重构的软件定义微纳卫星需求,需要突破传统卫星平台和传统光学相机的设计局限,开展基于微纳卫星的软件定义下新型计算光学成像载荷技术研究。充分考虑有效载荷的软件和硬件两者之间联合设计可能存在的发展空间,分析了亚像元信息、卫星平台参数、光学系统参数、探测器参数、噪声、大气对图像数据处理,特别是超分辨率重建的影响。根据各个影响因素的物理机制分别建立物理模型和误差模型,作为重建方法的先验信息,将这些有利于超分辨技术的先验信息约束应用于相机设计过程,使得相机获取的图像可以很好地匹配超分辨方法。该方法可以提升视觉分辨率和实质分辨率,同时保持对噪声的抑制能力,并有可能降低传统相机的结构尺寸和研制难度。研制实现集超分辨成像、动态范围增强成像、视频成像等软件智能可控的多种成像处理模式于一体的通用型计算光学成像相机,将对航天产业提供更大的灵活性和增值空间,为未来智能卫星航天技术研究与快速创新提供一种可行的方案。

关键词: 软件定义卫星, 超分辨, 动态范围增强, 视频成像, 计算光学成像

Abstract: In order to accomplish the software-defined micro-nano satellite demands, which includes that its payload functions and parameters could be reconstructive and controllable by uploading software as needs, we have to break through the design limitations between traditional satellite platform and ordinary optical camera, and one new type of optical imaging camera technology is developed based on software-defined micro-nano satellite here. We gave full consideration to the possible development of joint design space between the software and the hardware of the payload. Then we analyzed the influence of sub-pixel information, satellite platform parameters, optical system parameters, detector parameters, noise and atmosphere on image data processing, especially the super-resolution reconstruction. We established the physical model and the error model according to the physical mechanism of each factor, as priori information of the reconstruction method.We applied these prior information constraints in favor of super-resolution to the design of the camera, enabling the images captured by the camera to match the super-resolution method very well. This method can simultaneously improve visual resolution and substantial resolution while maintaining the ability of suppressing noise, and may reduce the size and development difficulty of traditional cameras. We have developed a general purpose computing optical imaging camera, which integrates the super resolution imaging, dynamic range enhanced imaging, video imaging and other multi intelligent controllable imaging modes. Finally we have completed the related camera integration, testing and experiment.

Key words: software-defined satellite, super-resolution, dynamic range enhancement, video imaging, computational optical imaging

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