摘要
光子计数激光雷达数据中噪声点云过多的问题严重制约了光子雷达的实际应用,为了解决该问题,针对推扫式光子雷达探测体制和光子点云数据分布的特点,提出一种去噪方法。首先根据点云数据集的空间分布设定密度阈值进行粗去噪;然后计算探测激光束的斜率,将剩余数据划分成不同区间,再结合最大密度点设定距离阈值,对各区间进行进一步去噪;最后针对部分区间使用统计滤波进行最终去噪。实验结果显示,所提方法对试验区目标点云的识别率达98.2%,去噪率达93.8%,可以有效地去除光子数据中的噪声点云,较为完整地保留信号点云。
Excessive noise point cloud in photon-counting lidar data severely restricts the practical application of photon radar. To solve this problem, this paper proposes a denoising method for the detection system of push-broom photon radar and the characteristics of photon point cloud data distribution. First, we set the density threshold based on the spatial distribution of the point cloud dataset for rough denoising. Then, we calculated the slope of the detection laser beam to classify the remaining data into different intervals. Next, we combined the maximum density point to set the distance threshold for further denoising each interval. Finally, we used statistical filtering for the final denoising of some intervals. The experimental results show that the target point cloud recognition rate of the proposed method reaches 98. 2% in the test area and the denoising rate reaches 93. 8%. Thus, the proposed method can remove the noise point cloud in the photon data effectively and retain the signal point cloud relatively completely.
作者
魏硕
赵楠翔
胡以华
李敏乐
孙万顺
Wei Shuo;Zhao Nanxiang;Hu Yihua;Li Minle;Sun Wanshun(State Key Laboratory of Pulsed Power Laser Technology,Electronic Warfare Academy,National University of Defense Technology,Hefei 230037,Anhui,China;Advanced Laser Technology,Hefei 230037,Anhui,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2022年第12期106-112,共7页
Laser & Optoelectronics Progress
基金
国防科技大学科研计划(ZK18-01-02)
脉冲功率激光技术国家重点实验室主任基金(SKL2018ZR09)。
关键词
图像处理
激光技术
光子雷达
去噪
统计滤波
推扫式
image processing
laser technique
photon radar
denoising
statistical filtering
push-broom
作者简介
通信作者:赵楠翔,southfly@163.com。
