An Anti-Noise-Designed Residual Phase Unwrapping Neural Network for Digital Speckle Pattern Interferometry
Abstract
:1. Introduction
2. Anti-Noise-Designed Residual U-Net Phase Unwrapping Network Design
2.1. Residiual Block
2.2. U-Net Phase Unwrapping Network
2.3. Neural Network Architecture
2.4. SSIM Loss Function
3. Dataset Establishment, Network Training, and Enhancement
3.1. Dataset Establishment
3.2. Network Implementation Details, Tables, and Schemes
3.3. Network Training Process
3.4. Image Stitching Function Design
4. Experimental Results and Analysis
4.1. Image Results of Simulation and Experimental Data Testing
4.2. Result Analysis and Effectiveness Verification
5. Conclusions and Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Unwrapping Method | 256 × 256 | 512 × 512 | 1024 × 1024 |
---|---|---|---|
Algorithm based on spiral path | 0.21 | 0.24 | 0.4237 |
Algorithm based on reliability | 0.31 | 6.5 | 74.84 |
Res-unet | 1.087 | 1.085 | 1.169 |
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Wang, B.; Cao, X.; Lan, M.; Wu, C.; Wang, Y. An Anti-Noise-Designed Residual Phase Unwrapping Neural Network for Digital Speckle Pattern Interferometry. Optics 2024, 5, 44-55. https://doi.org/10.3390/opt5010003
Wang B, Cao X, Lan M, Wu C, Wang Y. An Anti-Noise-Designed Residual Phase Unwrapping Neural Network for Digital Speckle Pattern Interferometry. Optics. 2024; 5(1):44-55. https://doi.org/10.3390/opt5010003
Chicago/Turabian StyleWang, Biao, Xiaoling Cao, Meiling Lan, Chang Wu, and Yonghong Wang. 2024. "An Anti-Noise-Designed Residual Phase Unwrapping Neural Network for Digital Speckle Pattern Interferometry" Optics 5, no. 1: 44-55. https://doi.org/10.3390/opt5010003