Measurement Matrix Construction for Large-area Single Photon Compressive Imaging
Abstract
:1. Introduction
2. Principle and Realization of Experimental System
3. Construction of Measurement Matrix and Theoretical Analysis
3.1. Construction of Measurement Matrix
3.2. Theoretical Analysis of Matrix Performance
4. Experimental Performance Verification
4.1. Influence of Sparsity Ratio on Imaging Quality
4.2. Influence of Compressive Sampling Ratio on Imaging Quality
4.3. Comparison of Imaging Performance of Different Measurement Matrices
4.4. Influence of Poisson Noise on Imaging Quality
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Evaluation Index | MSE | PSNR | MSSIM |
---|---|---|---|
Sparse binary random matrix | 29.6249 | 33.3144 | 0.8607 |
m sequence matrix | 16.3040 | 36.0078 | 0.9081 |
True random number matrix | 27.3209 | 33.7658 | 0.8685 |
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Wang, H.; Yan, Q.; Li, B.; Yuan, C.; Wang, Y. Measurement Matrix Construction for Large-area Single Photon Compressive Imaging. Sensors 2019, 19, 474. https://doi.org/10.3390/s19030474
Wang H, Yan Q, Li B, Yuan C, Wang Y. Measurement Matrix Construction for Large-area Single Photon Compressive Imaging. Sensors. 2019; 19(3):474. https://doi.org/10.3390/s19030474
Chicago/Turabian StyleWang, Hui, Qiurong Yan, Bing Li, Chenglong Yuan, and Yuhao Wang. 2019. "Measurement Matrix Construction for Large-area Single Photon Compressive Imaging" Sensors 19, no. 3: 474. https://doi.org/10.3390/s19030474
APA StyleWang, H., Yan, Q., Li, B., Yuan, C., & Wang, Y. (2019). Measurement Matrix Construction for Large-area Single Photon Compressive Imaging. Sensors, 19(3), 474. https://doi.org/10.3390/s19030474