量子电子学报 ›› 2025, Vol. 42 ›› Issue (6): 770-778.doi: 10.3969/j.issn.1007-5461.2025.06.004

• 图像与信息处理 • 上一篇    下一篇

远距离单光子快速成像算法

郎昌财 , 刘尉悦 *   

  1. 宁波大学信息科学与工程学院, 浙江 宁波 315211
  • 收稿日期:2023-10-17 修回日期:2024-01-09 出版日期:2025-11-28 发布日期:2025-11-28
  • 通讯作者: E-mail: liuweiyue@nbu.edu.cn E-mail:liuweiyue@nbu.edu.cn
  • 作者简介:郎昌财 ( 1997 - ), 安徽芜湖人, 研究生, 主要从事量子通信与应用方面的研究。E-mail: 1832955773@qq.com
  • 基金资助:
    浙江省自然科学基金 (LY21F050003)

Long‐distance single‐photon fast imaging algorithm

LANG Changcai, LIU Weiyue *   

  1. Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
  • Received:2023-10-17 Revised:2024-01-09 Published:2025-11-28 Online:2025-11-28
  • Supported by:

摘要: 单光子探测已广泛应用于远距离三维成像领域, 但由于回波光子少和高背景噪声的原因, 使得远距离成像 面临成像模糊和成像时间长等挑战。针对此问题, 基于现有远距离单光子成像模型, 本研究提出了一种光子效率高、 成像速度快的远距离成像算法。在不同噪声水平下, 开展了模拟对比实验, 结果表明, 与目前最先进的方法相比, 尤 其是在低信号背景比和光子数约为1的条件下, 本算法成像时间得以大幅缩短。在真实的45 km距离场景中, 本算法 深度重建图的均方根误差ERMS为1.16 m, 重建时间为1.38 s。

关键词: 量子光学, 远距离成像, 泊松过程, 单光子探测, 实时成像, 深度重建

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

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