Deblurring of Beamformed Images in the Ocean Acoustic Waveguide Using Deep Learning-Based Deconvolution
Abstract
:1. Introduction
2. Materials and Methods
2.1. Conventional Beamforming Using a Linear Receiver Array
2.2. Deconvolution Using Neural Network
2.3. Data Simulation Method
Algorithm 1: Midpoint Displacement in OneDimension |
2.4. Experiment
3. Results
3.1. Synthetic Data
3.2. Experimental Data
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
References
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Zha, Z.; Yan, X.; Ping, X.; Wang, S.; Wang, D. Deblurring of Beamformed Images in the Ocean Acoustic Waveguide Using Deep Learning-Based Deconvolution. Remote Sens. 2024, 16, 2411. https://doi.org/10.3390/rs16132411
Zha Z, Yan X, Ping X, Wang S, Wang D. Deblurring of Beamformed Images in the Ocean Acoustic Waveguide Using Deep Learning-Based Deconvolution. Remote Sensing. 2024; 16(13):2411. https://doi.org/10.3390/rs16132411
Chicago/Turabian StyleZha, Zijie, Xi Yan, Xiaobin Ping, Shilong Wang, and Delin Wang. 2024. "Deblurring of Beamformed Images in the Ocean Acoustic Waveguide Using Deep Learning-Based Deconvolution" Remote Sensing 16, no. 13: 2411. https://doi.org/10.3390/rs16132411