Abstract: Single-photon detection has been used in the field of long-distance three-dimensional imaging. However, due to the low number of echo photons and high background noise, long-distance single-photon imaging faces challenges such as image blurring and long imaging time. To address this issue, based on the existing long-distance single-photon imaging models, a long-distance computational imaging algorithm with high photon efficiency and faster imaging speed is proposed in this work, and the simulated comparative experiments at different noise levels are conducted. The results show that, compared with the current state-of-the-art methods, the proposed algorithm can significantly shorten the imaging time, especially under the conditions of low signal-to-background ratio and a photon count of approximately 1. In a real 45 km distance scenario, using the proposed algorithm, the root mean square error (ERMS) of the depth reconstruction map is 1.16 m, and the reconstruction time is 1.38 s.

Key words: quantum optics, long-distance imaging, Poisson process, single-photon detection, real-time imaging, depth reconstruction