Laser & Optoelectronics Progress, Volume. 57, Issue 10, 101105(2020)

Compressive Computational Ghost Imaging Method Based on Region Segmentation

Wei Feng1,2、*, Xiaodong Zhao1, Shaojing Tang1, and Daxing Zhao1
Author Affiliations
  • 1School of Mechanical Engineering, Hubei University of Technology, Wuhan, Hubei 430068, China
  • 2Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan, Hubei 430068, China
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    Figures & Tables(7)
    Schematic of RSCCGI
    Flow chart of proposed method
    Simulation results. (a) Measured object; (b) binary random speckle pattern preset in DMD
    ROI recognition results with different sampling rates. (a) β=0.05; (b) β=0.10
    Results of image segmentation
    Comparison chart of numerical simulation results of different methods at different sampling rates. (a) β=0.05; (b) β=0.10; (c) β=0.20; (d) β=0.30
    Curves of different indicators and sampling times. (a) PSNR; (b) SSIM
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    Wei Feng, Xiaodong Zhao, Shaojing Tang, Daxing Zhao. Compressive Computational Ghost Imaging Method Based on Region Segmentation[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101105

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    Paper Information

    Category: Imaging Systems

    Received: Aug. 29, 2019

    Accepted: Oct. 18, 2019

    Published Online: May. 8, 2020

    The Author Email: Wei Feng (david2018@hbut.edu.cn)

    DOI:10.3788/LOP57.101105

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