A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network
Abstract
:1. Introduction
2. pu-pix2pix
2.1. The Principle of Phase Unwrapping
2.2. pix2pix Model
2.3. The Structure of pu-pix2pix
2.4. Loss Function
3. Experiments and Results
3.1. Dataset Generation
- (1)
- Simulate the topography phase. There are two methods for this: one is to specify the size and elevation range of the row and column, and generate an analog digital elevation model according to the random polynomial to obtain the topography phase image; the other is to use the existing DEM (digital elevation model) data, then simulate the oblique range imaging process of dual-antenna SAR sensors, specify the baseline length, and obtain a phase image containing only terrain errors, which is considered to be a true terrain phase image.
- (2)
- Simulate the atmospheric phase noise. The power spectrum inversion method is used to simulate this atmospheric phase noise. Its basic principle is to filter the complex Gauss random number matrix with a power spectrum function consistent with atmospheric turbulence, and then use the inverse Fourier transform to obtain the atmospheric phase noise.
- (3)
- Phase rewrapped. To perform the phase rewrapped operation, combine the terrain phase result with the atmospheric phase, and wrap the phase value to .
- (4)
- Add noise. The gamma distribution is used to simulate the InSAR phase noise, and the wrapped phase image is noised to obtain the wrapped phase image with noise.
- (5)
- Merge the images. To meet the input conditions of the pu-pix2pix model’s paired image training, first cut the phase diagram and the wrapped phase diagram with noise to 256 × 256 size, and then combine them into multiple 256 × 512 size images.
3.2. Performance Evaluation Index
3.3. Experimental Settings
3.4. Analysis of Unwrapping Results Based on Simulated Data
3.5. Analysis of Unwrapping Results Based on Real Data
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Method | RMSE (Rad) | Time (s) |
---|---|---|
Quality guide | 5.5797 | 1.3982 |
LS | 5.0503 | 1.1495 |
MCF | 1.8911 | 3.2251 |
U-net | 1.5424 | 0.1474 |
pix2pix | 1.5514 | 0.1517 |
pu-pix2pix | 1.5129 | 0.1526 |
Method | The First Set of Real Data | The Second Set of Real Data | ||
---|---|---|---|---|
RMSE (Rad) | Time (s) | RMSE (Rad) | Time (s) | |
Quality guide | 14.3751 | 1.4734 | 4.1260 | 1.3154 |
LS | 13.0493 | 1.3549 | 9.6236 | 1.3241 |
MCF | 2.7510 | 4.0452 | 2.8114 | 3.3454 |
U-net | 2..9514 | 0.1621 | 2.5786 | 0.1579 |
pix2pix | 2.2513 | 0.1645 | 2.1568 | 0.1631 |
pu-pix2pix | 2.2207 | 0.1631 | 2.1321 | 0.1570 |
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Zhang, L.; Huang, G.; Li, Y.; Yang, S.; Lu, L.; Huo, W. A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network. Remote Sens. 2023, 15, 4885. https://doi.org/10.3390/rs15194885
Zhang L, Huang G, Li Y, Yang S, Lu L, Huo W. A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network. Remote Sensing. 2023; 15(19):4885. https://doi.org/10.3390/rs15194885
Chicago/Turabian StyleZhang, Long, Guoman Huang, Yutong Li, Shucheng Yang, Lijun Lu, and Wenhao Huo. 2023. "A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network" Remote Sensing 15, no. 19: 4885. https://doi.org/10.3390/rs15194885