Chinese Optics Letters, Volume. 22, Issue 4, 041101(2024)

Non-blind super-resolution reconstruction for laser-induced damage dark-field imaging of optical elements

Qian Wang1, Fengdong Chen1、*, Yueyue Han1, Fa Zeng2、**, Cheng Lu1, and Guodong Liu1、***
Author Affiliations
  • 1Instrument Science and Technology, Harbin Institute of Technology, Harbin 150001, China
  • 2Research Center of Laser Fusion, China Academy of Engineering Physics, Mianyang 621900, China
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    Figures & Tables(12)
    Examples of LIDs on an optical element. Images above the dark-field image are the corresponding LIDs captured by a microscope.
    Principle of the multichannel and multifrequency mixing deconvolution method.
    Workflow of the PSF measurement algorithm[12].
    Principle of the PSF measurement considering the inconsistency at different positions and slight defocus.
    Sketch of the MMFDNet network structure.
    Measured PSFs in typical position (d = 255 mm).
    SR reconstruction results. The first column shows the low-resolution sample input images; the second column shows the high-resolution GT images; the third column shows the SR results of NAFNet; the fourth column shows the SR results of MMFDNet (ours). The data on the image are the PSNR (in dB)/SSIM values.
    Result of the adaptive mean threshold segmentation that is used as the damage attention region.
    Search results for the ω. The black dashed line indicates the results of training using the Loss1 function on both PSNR and SSIM values. Other lines represent PSNR and SSIM values when ω takes different values.
    Comparison of the SR results on low-resolution images acquired by actual cameras.
    • Table 1. Results of NAFNet and MMFDNet (ours) of Partial Samples

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      Table 1. Results of NAFNet and MMFDNet (ours) of Partial Samples

       NAFNetMMFDNet (ours)
       PSNR/dBSSIMPSNR/dBSSIM
      Input139.2370.98539.9710.988
      Input239.5430.98340.1910.984
      Input337.1260.98438.5840.987
      Input437.2610.99139.3700.993
      Input539.7430.98941.2420.990
      Input635.6280.98137.9490.985
      Input735.9090.97238.2910.982
    • Table 2. Performance of the Networks and Loss Functions on the Data Set

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      Table 2. Performance of the Networks and Loss Functions on the Data Set

       Loss1LossregionPSNR/dBSSIM
      NAFNet37.2400.9809
      37.4970.9816
      MMFDNet38.2020.9833
      38.5730.9840
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    Qian Wang, Fengdong Chen, Yueyue Han, Fa Zeng, Cheng Lu, Guodong Liu, "Non-blind super-resolution reconstruction for laser-induced damage dark-field imaging of optical elements," Chin. Opt. Lett. 22, 041101 (2024)

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    Paper Information

    Category: Imaging Systems and Image Processing

    Received: Oct. 17, 2023

    Accepted: Dec. 11, 2023

    Posted: Dec. 14, 2023

    Published Online: May. 6, 2024

    The Author Email: Fengdong Chen (chenfd@hit.edu.cn), Fa Zeng (cengfa@tsinghua.org.cn), Guodong Liu (lgd@hit.edu.cn)

    DOI:10.3788/COL202422.041101

    CSTR:32184.14.COL202422.041101

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