Jinxin XU, Qingwu LI, Zhiqiang GUAN, Xiaolin WANG. Nonlinear Reconstruction for Target Density Based on Randomly Perturbed Optimization and Multi-models Fusion[J]. Acta Photonica Sinica, 2022, 51(3): 0310006
- Acta Photonica Sinica
- Vol. 51, Issue 3, 0310006 (2022)
Fig. 1. First derivative products of different forward models
Fig. 2. ACF and IACT of sample estimation for each algorithm
Fig. 3. The RE of sample estimation and reconstructed time by each algorithm
Fig. 4. The RE involving multi-model fusion
Fig. 5. Reconstructed results of FTO transmission image with variable density （1.25% noise level）
Fig. 6. Reconstructed results of FTO transmission image with constant density （1.25% noise level）
Fig. 7. High energy flash X-ray static image under 4 MeV
Fig. 8. Results of density reconstruction （4 MeV static image）
Fig. 9. Comparison of reconstructed density profiles of each algorithm
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Table 1. The PSNR and SSIM of reconstructed results of constant density FTO images
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Table 2. The PSNR and SSIM of reconstructed results of variable density FTO images
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Table 3. Average value （g/cm3）and relative error （%）of density reconstruction of each algorithm
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