Laser & Optoelectronics Progress, Volume. 60, Issue 22, 2211003(2023)

Computational Ghost Imaging Method Based on Discrete W Transform

Qifei Zhang1, Rui Sun2, Yi Ding2、*, Jiaye Kuang2, and Baolin Sun1
Author Affiliations
  • 1School of Information Engineering, Hubei University of Economics, Wuhan 430205, Hubei, China
  • 2Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen 529020, Guangdong, China
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    Figures & Tables(14)
    Comparison of two sets of illumination patterns (M=N=128). (a) Patterns generated from equation (8); (b) patterns generated from equation (9)
    Procedure of computational ghost imaging based on DWT
    Comparison of reconstruction results for the USAF image by different methods
    Reconstruction results for the USAF image under different noise levels
    Reconstructed images of grayscale and binary DWT-CGI under different sampling ratios
    RPSNR values of grayscale and binary DWT-CGI under different sampling ratios
    Comparison of reconstruction results for the USAF image by different methods
    Schematic of the experimental system
    Reconstruction results for the USAF and toy pig by DCT-CGI and DWT-CGI
    Reconstruction results for the USAF and toy duck by DCT-CGI and DWT-CGI
    • Table 1. Quantitative comparison results for the USAF image by different methods

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      Table 1. Quantitative comparison results for the USAF image by different methods

      IndexMethodSampling ratio /%
      5101520
      RPSNR /dBDCT-CGI13.0315.7517.7219.38
      FCGI12.7814.9616.9818.60
      DWT-CGI13.1315.9317.7919.53
      MSSIM /%DCT-CGI29.5951.0364.7072.83
      FCGI30.4750.1463.7172.80
      DWT-CGI30.1150.7165.4773.23
    • Table 2. Comparison of image reconstruction time by different methods

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      Table 2. Comparison of image reconstruction time by different methods

      Sampling ratioDWT-CGIDCT-CGIFCGI
      5%0.0010710.0015750.009257
      10%0.0010790.0020200.017320
      15%0.0016260.0024470.019452
      20%0.0012450.0019190.015926
    • Table 3. Quantitative comparison results for the USAF image under different noise levels

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      Table 3. Quantitative comparison results for the USAF image under different noise levels

      IndexMethodRSNR /dB
      0-10-20-30
      RPSNR /dBDCT-CGI18.0615.269.987.22
      FCGI18.9414.8310.427.26
      DWT-CGI19.5115.7210.537.62
      MSSIM /%DCT-CGI46.9941.8725.9311.11
      FCGI48.1341.9328.2713.73
      DWT-CGI48.7942.7227.0212.08
    • Table 4. Quantitative comparison results for the USAF image by different methods

      View table

      Table 4. Quantitative comparison results for the USAF image by different methods

      IndexMethodSampling ratio /%
      5101520
      DCT-CGI12.9915.6017.3818.76
      RPSNR /dBFCGI12.7514.8716.7618.18
      DWT-CGI13.0915.7817.4518.90
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    Qifei Zhang, Rui Sun, Yi Ding, Jiaye Kuang, Baolin Sun. Computational Ghost Imaging Method Based on Discrete W Transform[J]. Laser & Optoelectronics Progress, 2023, 60(22): 2211003

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    Paper Information

    Category: Imaging Systems

    Received: Jan. 30, 2023

    Accepted: Mar. 6, 2023

    Published Online: Nov. 16, 2023

    The Author Email: Ding Yi (dingyi1688@126.com)

    DOI:10.3788/LOP230545

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