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Laser & Optoelectronics Progress, Volume. 58, Issue 10, 1011032(2021)

Hadamard Ghost Imaging Based on Compressed Sensing Reconstruction Algorithm

Chang Li, Chao Gao, Jiaqi Shao, Xiaoqian Wang*, and Zhihai Yao**
Author Affiliations
  • College of Science, Changchun University of Science and Technology, Changchun, Jilin 130022, China
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    Figures&Tables (16)
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    References (27)
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    Figures & Tables(16)
    Experimental setup for computational ghost imaging

    Fig. 1. Experimental setup for computational ghost imaging

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    Original image of five-pointed star

    Fig. 2. Original image of five-pointed star

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    CGI reconstructed image of five-pointed star using the correlation algorithm when the reconstruction times is 200 and K=19.5%

    Fig. 3. CGI reconstructed image of five-pointed star using the correlation algorithm when the reconstruction times is 200 and K=19.5%

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    CSHGI reconstructed images of five-pointed star using SP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

    Fig. 4. CSHGI reconstructed images of five-pointed star using SP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

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    CSHGI reconstructed images of five-pointed star using OMP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

    Fig. 5. CSHGI reconstructed images of five-pointed star using OMP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

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    Original image of CUST

    Fig. 6. Original image of CUST

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    CGI reconstructed image of CUST using the correlation algorithm when the reconstruction times is 1000 and K=24.4%

    Fig. 7. CGI reconstructed image of CUST using the correlation algorithm when the reconstruction times is 1000 and K=24.4%

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    CSHGI reconstructed images of CUST using SP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 600 and K=14.6%; (b) the number of iterations is 800 and K=19.5%; (c) the number of iterations is 1000 and K=24.4%

    Fig. 8. CSHGI reconstructed images of CUST using SP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 600 and K=14.6%; (b) the number of iterations is 800 and K=19.5%; (c) the number of iterations is 1000 and K=24.4%

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    CSHGI reconstructed images of CUST using OMP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 600 and K=14.6%; (b) the number of iterations is 800 and K=19.5%; (c) the number of iterations is 1000 and K=24.4%

    Fig. 9. CSHGI reconstructed images of CUST using OMP reconstruction algorithm when the light source is Hadamard speckle. (a) The number of iterations is 600 and K=14.6%; (b) the number of iterations is 800 and K=19.5%; (c) the number of iterations is 1000 and K=24.4%

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    Schematic of CSHGI experiment

    Fig. 10. Schematic of CSHGI experiment

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    Object to be measured in the experiment

    Fig. 11. Object to be measured in the experiment

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    CSHGI reconstructed images using the SP reconstruction algorithm with Hadamard speckle in the experiment. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

    Fig. 12. CSHGI reconstructed images using the SP reconstruction algorithm with Hadamard speckle in the experiment. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

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    CSHGI reconstructed images using the OMP reconstruction algorithm with Hadamard speckle in the experiment. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

    Fig. 13. CSHGI reconstructed images using the OMP reconstruction algorithm with Hadamard speckle in the experiment. (a) The number of iterations is 100 and K=9.8%; (b) the number of iterations is 150 and K=14.6%; (c) the number of iterations is 200 and K=19.5%

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    • Table 1. Comparison of reconstruction results using two algorithms when the object to be measured is a binary image

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      Table 1. Comparison of reconstruction results using two algorithms when the object to be measured is a binary image

      Number of iterations50100150200250
      K/%4.99.814.619.524.4
      TSP/s0.3430.5431.5593.0947.594
      TOMP /s0.1720.2660.7341.5632.266
      SSSIM-SP0.25520.35340.50470.68880.7597
      SSSIM-OMP0.22770.33160.43680.68200.7476

    • Table 2. Comparison of reconstruction results using two algorithms when the object to be measured is a gray-scale image

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      Table 2. Comparison of reconstruction results using two algorithms when the object to be measured is a gray-scale image

      Number of iterations40060080010001200
      K/%9.814.619.524.429.3
      TSP/s79.058267.336391.707666.8901052.539
      TOMP /s16.06241.22182.532157.416254.331
      SSSIM-SP0.54490.69080.85520.92550.9369
      SSSIM-OMP0.51650.67220.79540.85040.8840

    • Table 3. Comparison of reconstruction results of two algorithms in the experiment

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      Table 3. Comparison of reconstruction results of two algorithms in the experiment

      Number of iterations50100150200250
      K/%4.99.814.619.524.4
      TSP/s0.1730.6421.5723.6716.678
      TOMP /s0.1630.3210.7031.4122.310
      SSSIM-SP0.20510.39000.49490.63960.7379
      SSSIM-OMP0.12680.29030.42400.61840.7215
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    Chang Li, Chao Gao, Jiaqi Shao, Xiaoqian Wang, Zhihai Yao. Hadamard Ghost Imaging Based on Compressed Sensing Reconstruction Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(10): 1011032

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    Paper Information

    Category: Imaging Systems

    Received: Apr. 1, 2021

    Accepted: Apr. 14, 2021

    Published Online: May. 28, 2021

    The Author Email: Xiaoqian Wang (xqwang21@163.com), Zhihai Yao (yaozh@cust.edu.cn)

    DOI:10.3788/LOP202158.1011032

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology