High Power Laser and Particle Beams, Volume. 36, Issue 6, 069002(2024)
Deep learning phase inversion technique for single frame image based on Walsh function modulation
Figures & Tables(15)
Fig. 2. Wavefront and far field intensity plots for positive and negative defocusing aberrations after modulation using partial Walsh functions
Fig. 9. Rotated 180° complex conjugate wavefront restoration results
Table 1. Comparison of test results of different Walsh function modulated sample training networks
View tableView in ArticleTable 1. Comparison of test results of different Walsh function modulated sample training networks
Walsh function ResNet18 RMSE/μm ResNet34 RMSE/μm ResNet50 RMSE/μm ResNet101 RMSE/μm W12 0.0115 0.0105 0.0080 0.0069 W15 0.0111 0.0092 0.0062 0.0067 W3 0.0103 0.0087 0.0055 0.0054
Table 2. Average RMS ratio with Zernike order wavefront
View tableView in ArticleTable 2. Average RMS ratio with Zernike order wavefront
Zernike levels average RMS ratio/% Zernike 4～10 9.6 Zernike 4～15 8.6 Zernike 4～20 8.5 Zernike 4～25 8.4 Zernike 4～30 7.8
Table 3. Average RMS ratio of far-field intensity map with different pixels
View tableView in ArticleTable 3. Average RMS ratio of far-field intensity map with different pixels
intensity image pixels average RMS ratio/% 256×256 7.8 512×512 10.2 1024×1024 12.9
Table 4. Average RMS ratio of noise samples under different models
View tableView in ArticleTable 4. Average RMS ratio of noise samples under different models
test data set samples for training purposes average RMS ratio of residual wavefront to original wavefront/% 256×256 with random noise samples 350 000 normal samples invalid 256×256 with random noise samples 350 000 normal samples+ 350 000 noise samples 6.5
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Qi Liu, Yinglei Du, Rujian Xiang, Guohui Li, Qiushi Zhang, Zhenjiao Xiang, Jing Wu, Xian Yue, Anchao Bao, Jiang You. Deep learning phase inversion technique for single frame image based on Walsh function modulation[J]. High Power Laser and Particle Beams, 2024, 36(6): 069002
Paper Information
Category: Advanced Interdisciplinary Science
Received: Feb. 1, 2024
Accepted: Mar. 28, 2024
Published Online: Jun. 3, 2024
The Author Email: Du Yinglei (boyduyinglei@163.com)
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