Imaging quality optimization of cross-strip anode single-photon detectors based on the three Gaussian algorithms

Cross-strip (XS) anode single-photon detectors are highly valuable for detecting distant dim targets owing to their excellent sensitivity and spatial resolution. However, traditional reconstruction algorithms (G3S and MCOG) suffer from severe imaging distortions. To address this issue, we propose a modified Gaussian 3 strip (MG3S) algorithm, developed through a combination of Monte Carlo simulations and practical experiments. Experimental results show that MG3S improves the imaging resolution from 55.7 µm (G3S) and 49.6 µm (MCOG) to 44.2 µm, increases the structural similarity index (SSIM) with the reference image from 0.0594 (G3S) and 0.0724 (MCOG) to 0.1412, and raises the peak signal-to-noise ratio (PSNR) from 7.857 dB (G3S) and 8.025 dB (MCOG) to 9.893 dB. These improvements result from the effective suppression of fixed-pattern noise and rejection of abnormal data. The robustness and computational complexity of the three algorithms are also compared. This work provides new insights, to our knowledge, into high-precision image reconstruction for XS anode single-photon detectors and enables accurate detection and imaging of distant dim space targets.