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
Fig. 1. Basic structure of the CUP-VISAR system for measuring shock wave velocity.
Fig. 2. Framework for coding matrix design utilizing a CVAE network.
Fig. 4. Mask. (a) Random mask; (b) 300 epoch feature-free fusion mask; (c) 300 epoch feature fusion mask.
Fig. 5. 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.
Fig. 6. Experimental mask plate specification drawing. The coding-aperture ratio of the mask is 7:3. (a) Feature fusion mask; (b) random mask.
Fig. 7. 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)
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)