Single Photon Compressive Imaging Based on Digital Grayscale Modulation Method
Chenglong Yuan , Qiurong Yan , Yiqiang Wu , Yifan Wang , Yuhao Wang
Photonic Sensors ›› 2020, Vol. 11 ›› Issue (3) : 350 -361.
Single Photon Compressive Imaging Based on Digital Grayscale Modulation Method
In single-pixel imaging or computational ghost imaging, the measurement matrix has a great impact on the performance of the imaging system, because it involves modulation of the optical signal and image reconstruction. The measurement matrix reported in the existing literatures is first binarized and then loaded onto the digital micro-mirror device (DMD) for optical modulation, that is, each pixel can only be modulated into on-off states. In this paper, we propose a digital grayscale modulation method for more efficient compressive sampling. On the basis of this, we demonstrate a single photon compressive imaging system. A control and counting circuit, based on field-programmable gate array (FPGA), is developed to control DMD to conduct digital grayscale modulation and count single-photon pulse output from the photomultiplier tube (PMT) simultaneously. The experimental results show that the imaging reconstruction quality can be improved by increasing the sparsity ratio properly and compressive sampling ratio (SR) of these gray-scale matrices. However, when the compressive SR and sparsity ratio are increased appropriately to a certain value, the reconstruction quality is usually saturated, and the imaging reconstruction quality of the digital grayscale modulation is better than that of binary modulation.
Single photon imaging / single pixel imaging / measurement matrix / grayscale modulation
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
Z. Zhang, X. Ma, and J. Zhong, “Single-pixel imaging by means of Fourier spectrum acquisition,” Nature Communications, 2015, DOI: https://doi.org/10.1038/ncomms7225. |
| [13] |
K. Taguchi and J. S. Iwanczyk, “Vision 20/20: Single photon counting x-ray detectors in medical imaging,” Medical Physics, 2013, DOI: https://doi.org/10.1118/1.4820371. |
| [14] |
|
| [15] |
M. J. Sun and J. M. Zhang, “Single-pixel imaging and its application in three-dimensional reconstruction: a brief review,” Sensors, 2019, DOI: https://doi.org/10.3390/s19030732. |
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
V. Tiwari, P. P. Bansod, and A. Kumar, “Designing sparse sensing matrix for compressive sensing to reconstruct high resolution medical images,” Cogent Engineering, 2015, DOI: https://doi.org/10.1080/23311916.2015.1017244. |
| [21] |
H. Nouasria and M. Et-tolba, “New constructions of Bernoulli and Gaussian sensing matrices for compressive sensing,” in 2017 International Conference on Wireless Networks and Mobile Communications (WINCOM), Morocco, December 25, 2017, pp. 1–6. |
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
T. Huang, Y. Z. Fan, and M. Hu, “Compressed sensing based on random symmetric Bernoulli matrix,” in 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC), China, May 19–21, 2017, DOI: https://doi.org/10.1109/YAC.2017.7967403. |
| [29] |
D. Dudley, W. M. Duncan, and J. Slaughter, “Emerging digital micromirror device (DMD) applications,” Proceedings of SPIE, 2003, DOI: f10.1117/12.480761. |
| [30] |
|
| [31] |
R. Höfling and E. Ahl, “ALP: Universal DMD controller for metrology and testing,” Proceedings of SPIE, 2004, DOI: 10.1117/12.528336. |
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|
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