压缩感知在光学成像领域的应用

Jun Ke, Linxia Zhang, Qun Zhou

科研成果: 期刊稿件文献综述同行评审

16 引用 (Scopus)

摘要

The early application of compressive sensing in optical imaging focuses on spatial compressive imaging. In recent years, increasing compressive imaging systems have employed detector array instead of a single detector for collecting measured values. Moreover, the scope of compressive imaging expands from two-dimensional space to three-dimensional ranging, high-speed imaging, multispectral imaging, ghost imaging, and holography imaging. Herein, we analyzed recent works on high-resolution compressive imaging, compressive sensing ranging, and temporal high-speed compressive imaging with details, summarized the research progresses of measured matrix design by combining spatial compressive imaging, works on sensing matrix design in spatial compressive imaging, discussed their challenges and future development opportunities, and reviewed the applications of compressive sensing in multispectral imaging, ghost imaging, and holography imaging. Furthermore, we summarized the improvement of reconstruction performance of system targets by applying deep learning to compressive imaging.

投稿的翻译标题Applications of Compressive Sensing in Optical Imaging
源语言繁体中文
文章编号0111006
期刊Guangxue Xuebao/Acta Optica Sinica
40
1
DOI
出版状态已出版 - 10 1月 2020

关键词

  • Compressive sensing
  • Computational imaging
  • Deep learning
  • High-speed camera
  • Imaging systems
  • Infrared imaging
  • Three-dimensional imaging

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