Chinese Optics Letters, Volume. 23, Issue 4, 041101(2025)

Feature fusion and variational autoencoder based deep coded aperture design for a CUP-VISAR diagnostic system

Miao Li*, Chenyan Wang, Xi Wang**, Lingqiang Zhang, Chaorui Chen, Zhaohui Guo, and Xueyin Zhao
Author Affiliations
  • School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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    Figures & Tables(7)
    Basic structure of the CUP-VISAR system for measuring shock wave velocity.
    Framework for coding matrix design utilizing a CVAE network.
    Network architecture diagram for encoding and decoding.
    Mask. (a) Random mask; (b) 300 epoch feature-free fusion mask; (c) 300 epoch feature fusion mask.
    Velocity fringe reconstruction of shock wave diagnosis by four algorithms with different masks. (a1) Random mask; (a2) measurement with the random mask; (a3)–(a6) 25th frame reconstruction of the random mask; (b1) feature-free fusion mask; (b2) measurement with the feature-free fusion mask; (a3)–(a6) 25th frame reconstruction of the feature-free fusion mask; (c1) feature fusion mask; (c2) measurement with feature fusion mask; (c3)–(c6) 25th frame reconstruction of the feature fusion mask.
    Experimental mask plate specification drawing. The coding-aperture ratio of the mask is 7:3. (a) Feature fusion mask; (b) random mask.
    Velocity fringe reconstruction performance in various coding aperture ratios. (a1), (b1) PSNR performance comparison for different algorithms; (a2), (b2) SSIM performance comparison for different algorithms.
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    Miao Li, Chenyan Wang, Xi Wang, Lingqiang Zhang, Chaorui Chen, Zhaohui Guo, Xueyin Zhao, "Feature fusion and variational autoencoder based deep coded aperture design for a CUP-VISAR diagnostic system," Chin. Opt. Lett. 23, 041101 (2025)

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    Paper Information

    Category: Imaging Systems and Image Processing

    Received: May. 21, 2024

    Accepted: Oct. 9, 2024

    Published Online: Apr. 11, 2025

    The Author Email: Miao Li (limiao@cqupt.edu.cn), Xi Wang (xiwang@cqupt.edu.cn)

    DOI:10.3788/COL202523.041101

    CSTR:32184.14.COL202523.041101

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