In this paper, we propose a photon counting ghost imaging scheme based on time-correlated single photon counting, and based on this scheme, Monte Carlo simulation is conduct with doubly Poisson stochastic process model ,the feasibility of traditional ghost imaging and corresponding ghost imaging is verified in this simulation, the influencing factors such as the number of frame M and the number of pulse within a single digital micro-mirror device(DMD) period D is also analyzed in the simulation. The results shows that the corresponding ghost imaging algorithm can effectively reduce the calculation amount when the imaging quality is close between the two algorithms, and the number of frames M has a greater influence on image quality. The model can effectively verify the feasibility of system design and improve the efficiency of the experiment, saving experiment time and costs.
KEYWORDS: Imaging systems, Monte Carlo methods, 3D image processing, Pulsed laser operation, Digital micromirror devices, Photon transport, Compressive imaging, 3D image reconstruction, 3D acquisition, 3D modeling
We propose a single-photon three-dimensional compressive imaging system based on TCSPC. The system uses compressive sensing instead of raster scanning to achieve high spatial resolution, and only two-dimensional reconstructions are required to image a three-dimensional scene. We also propose a system simulation model based on Monte Carlo, which is conduct with double poisson stochastic process model. In the simulation model, we studied the effects of imaging time, optical noise ratio, and gating algorithm on the imaging performance of the system. The results show that the single-photon compressive 3D imaging system based on TCSPC can image in 5 seconds. Noise gating can effectively improve the 3D imaging quality of the system. Our simulation provides a good choice of parameters for subsequent experiments. It has played a theoretical guiding role in the research and application of the actual three-dimensional imaging system.
We design a first-photon 3D Lidar system to solve the problem of reconstructing the target reflectivity and depth maps in low-light-level. The Monte Carlo method was used to simulate the photon counting model, mean value and gated filter algorithm for doubly stochastic Poisson point processes. The influence factors of reflectivity and depth imaging are light intensity, noise and scanning time, we simulated them and use gated filtering to suppress noise. The simulation results showed that the noise ratio, light intensity and scanning time all have impact on the reconstruct reflectivity and depth maps. if the light intensities and scanning time increase, noise ratio decrease, the image quality of target reflectivity and depth maps would improve. And the gated filtering can effectively suppress noise and improve the quality of target reflectivity and depth maps’ reconstruction. we simulate the system in order to verify the feasibility of the system design, provide reference and optimize to the design of system, save time and experimental costs.
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