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Objective Dynamic point target detection is vital in fields such as computer vision, remote sensing, and the military.With the technical development, there is an increasing demand for realtime and highly sensitive target detection, in which singlephoton imaging has great potential and application significance. Unfortunately, most currently available singlephoton detectors have only singlepixel or limited resolution, and traditional scanning imaging with these detectors cause time waste. Therefore, singlepixel singlephoton imaging based on compressed sensing has become a research hotspot. However, traditional singlephoton detection relies on photon number accumulation, which requires increased time to resist shot noise interference under the extremely low target signal, thus reducing detection speed. In recent years, firstphoton imaging technology has been proposed to achieve imaging by employing only one photon per pixel based on utilizing time information of the photon, but until now this technology can only be applied to active lidar systems, limiting its application scenarios. Thus, we propose a passive compressed sensing singlephoton imaging method for weak target detection, which utilizes firstphoton time information to improve the sensitivity and sampling speed of point target detection. Simulation analysis and experimental verification show that this method is feasible for highprecision imaging and positioning of weak targets in passive detection conditions and suitable for the simultaneous detection of multiple moving point targets. Our study is of great significance for improving the performance of weak target detection technology.Methods Firstly, we analyze the statistical relationship between the firstphoton time and average photon number under the influence of shot noise in singlephoton detection. The results show that as the average photon number increases, the probability of a smaller firstphoton time increases (Fig. 1). Based on this, a point target detection method based on compressed sensing imaging with firstphoton time measurement is proposed. This method employs a digital micromirror device (DMD) to spatially modulate a target with photon level and measures the arrival time of the first photon on the singlephoton detector after each modulation (Fig. 2). By setting a threshold, the corresponding relationship between the target position and the modulation matrix is estimated using the firstphoton time, leading to a binary measurement result of 0 or 1. Then, the targetrelated information can be extracted from the single photon detected after each modulation. By adopting the estimation results and modulation matrices, the point target image is reconstructed via a compressed sensing algorithm to achieve target position detection. Finally, a denoising algorithm based on frame difference is proposed to calculate the intensity difference between the neighbor pixels in adjacent frames and thus identify a reconstructed point as a target or noise point with a set threshold. As a result, the reconstructed...
Objective Dynamic point target detection is vital in fields such as computer vision, remote sensing, and the military.With the technical development, there is an increasing demand for realtime and highly sensitive target detection, in which singlephoton imaging has great potential and application significance. Unfortunately, most currently available singlephoton detectors have only singlepixel or limited resolution, and traditional scanning imaging with these detectors cause time waste. Therefore, singlepixel singlephoton imaging based on compressed sensing has become a research hotspot. However, traditional singlephoton detection relies on photon number accumulation, which requires increased time to resist shot noise interference under the extremely low target signal, thus reducing detection speed. In recent years, firstphoton imaging technology has been proposed to achieve imaging by employing only one photon per pixel based on utilizing time information of the photon, but until now this technology can only be applied to active lidar systems, limiting its application scenarios. Thus, we propose a passive compressed sensing singlephoton imaging method for weak target detection, which utilizes firstphoton time information to improve the sensitivity and sampling speed of point target detection. Simulation analysis and experimental verification show that this method is feasible for highprecision imaging and positioning of weak targets in passive detection conditions and suitable for the simultaneous detection of multiple moving point targets. Our study is of great significance for improving the performance of weak target detection technology.Methods Firstly, we analyze the statistical relationship between the firstphoton time and average photon number under the influence of shot noise in singlephoton detection. The results show that as the average photon number increases, the probability of a smaller firstphoton time increases (Fig. 1). Based on this, a point target detection method based on compressed sensing imaging with firstphoton time measurement is proposed. This method employs a digital micromirror device (DMD) to spatially modulate a target with photon level and measures the arrival time of the first photon on the singlephoton detector after each modulation (Fig. 2). By setting a threshold, the corresponding relationship between the target position and the modulation matrix is estimated using the firstphoton time, leading to a binary measurement result of 0 or 1. Then, the targetrelated information can be extracted from the single photon detected after each modulation. By adopting the estimation results and modulation matrices, the point target image is reconstructed via a compressed sensing algorithm to achieve target position detection. Finally, a denoising algorithm based on frame difference is proposed to calculate the intensity difference between the neighbor pixels in adjacent frames and thus identify a reconstructed point as a target or noise point with a set threshold. As a result, the reconstructed...
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