Acta Optica Sinica, Volume. 38, Issue 7, 0711001(2018)

Compressive Sensing Ghost Imaging Based on Neighbor Similarity

Yi Chen1,2、*, Xiang Fan1, Yubao Cheng1, Zhengdong Cheng1, and Zhenyu Liang1
Author Affiliations
  • 1 State Key Laboratory of Pulsed Power Laser Technology, National University of Defense Technology, Hefei, Anhui 230037, China
  • 2 Key Laboratory of Photoelectric Information Control and Safety Technology, Tianjin 300450, China
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    Figures & Tables(7)
    Experimental setup of NSGI
    Flowchart of NSGI algorithm
    Numerical simulation results of three images under different sampling rates
    Relationship between (a) PSNR, (b) imaging time and sampling rate
    Experimental results. (a) Original image; (b) NSGI; (C) CGI-OMP; (d) CGI-IHT; (e) CGI-IRLS; (f) CGI-CoSaMP
    • Table 1. Performance statistics of algorithms under different sampling rates

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      Table 1. Performance statistics of algorithms under different sampling rates

      ImageSampling ratePSNR /dBt /s
      NSGICGI-OMPNSGICGI-OMP
      Lena0.160.6265.290.17930.1811
      0.262.4068.810.30180.4666
      0.365.3969.670.53141.8505
      House0.152.2855.710.15980.1319
      0.254.0459.970.29500.3588
      0.357.1661.020.569908969
      Bridge0.150.1051.330.19360.2211
      0.253.1555.260.34000.4026
      0.357.4057.150.66592.4670
    • Table 2. Comparison of running performance of different algorithms

      View table

      Table 2. Comparison of running performance of different algorithms

      AlgorithmPSNR /dBt /s
      NSGI61.211.2408
      CGI-OMP55.230.5458
      CGI-IHT53.130.6971
      CGI-IRLS59.34141.4051
      CGI-CoSaMP55.713.0253
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    Yi Chen, Xiang Fan, Yubao Cheng, Zhengdong Cheng, Zhenyu Liang. Compressive Sensing Ghost Imaging Based on Neighbor Similarity[J]. Acta Optica Sinica, 2018, 38(7): 0711001

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    Paper Information

    Category: Imaging Systems

    Received: Dec. 10, 2017

    Accepted: --

    Published Online: Sep. 5, 2018

    The Author Email: Chen Yi (lishuichenyi@sina.com)

    DOI:10.3788/AOS201838.0711001

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