基于稀疏正则化的单光子激光雷达成像重构算法

doi:10.3969/j.issn.1007-5461.2026.05.008

量子电子学报 ›› 2026, Vol. 43 ›› Issue (5): 760-768.doi: 10.3969/j.issn.1007-5461.2026.05.008

基于稀疏正则化的单光子激光雷达成像重构算法

陈泽 1, 时东锋 2,3, 陈亚峰 2,3*

1 安徽大学电气工程与自动化学院, 安徽合肥 230601; 2 中国科学院合肥物质科学研究院安徽光学精密机械研究所, 中国科学院大气光学重点实验室, 安徽合肥 230031; 3 先进激光技术安徽省实验室, 安徽合肥 230037

收稿日期:2024-01-26 修回日期:2024-03-10 出版日期:2026-09-28 发布日期:2026-09-30
通讯作者: E-mail: yfchen@aiofm.ac.cn E-mail:yfchen@aiofm.ac.cn
作者简介:陈泽 ( 1999 - ), 江苏南通人, 研究生, 主要从事计算光学成像方面的研究。E-mail: keras_chan@163.com
基金资助:
中国科学院合肥研究院院长基金 (YZJJ202303-TS)

Single‐photon lidar imaging reconstruction algorithm based on sparse regularization

CHEN Ze 1, SHI Dongfeng 2,3, CHEN Yafeng 2,3*

1 School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China; 2 Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; 3 Advanced Laser Technology Laboratory of Anhui Province, Hefei 230037, China

Received:2024-01-26 Revised:2024-03-10 Published:2026-09-28 Online:2026-09-30

摘要/Abstract

摘要： 时间相关单光子计数技术是一种弱光信号检测方法, 具有光子级探测精度和皮秒级时间分辨率, 被广泛应用于激光雷达成像领域。然而, 传统成像算法在细节信息处理和光子利用率等方面均存在一定的局限, 因此制约了单光子激光雷达的性能。针对该问题, 本文从单光子激光雷达探测原理出发, 搭建了一套双轴振镜扫描式单光子激光雷达成像系统, 并提出一种基于稀疏正则化的最大后验概率估计算法。研究结果表明, 与传统中值滤波算法相比, 本文所提算法在降噪和细节保留方面效果显著, 反射率图像质量提升14.1%, 深度图像质量提升51.9%, 同时缩短了图像重构时间。

关键词: 量子光学, 稀疏正则化, 时间相关单光子计数, 三维成像, 激光雷达

Abstract: Time-correlated single-photon counting is a method for detecting weak light signals, offering photon-level detection accuracy and picosecond time resolution, and is widely used in lidar imaging. However, traditional imaging algorithms have certain limitations in edge information processing and photon utilization, which restrict the performance of single-photon lidar. To address this bottleneck, a dual-axis galvanometer scanning single-photon lidar imaging system was built based on the detection principle of single-photon lidar, and a Maximum A Posteriori estimation algorithm based on sparse regularization was proposed in this work. The results show that, compared with the traditional median filtering algorithm, the proposed imaging algorithm is more effective in noise reduction and detail preservation, with a 14.1% improvement in reflectivity image quality and a 51.9% improvement in depth image quality, while the image reconstruction time is reduced.

Key words: quantum optics, sparse regularization, time-correlated single-photon counting, 3D imaging; lidar

中图分类号:

O431.2

陈泽 , 时东锋 , 陈亚峰 , . 基于稀疏正则化的单光子激光雷达成像重构算法[J]. 量子电子学报, 2026, 43(5): 760-768.

CHEN Ze , SHI Dongfeng , CHEN Yafeng , . Single‐photon lidar imaging reconstruction algorithm based on sparse regularization[J]. Chinese Journal of Quantum Electronics, 2026, 43(5): 760-768.

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基于稀疏正则化的单光子激光雷达成像重构算法

Single‐photon lidar imaging reconstruction algorithm based on sparse regularization

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