基于改进DBSCAN的星载激光雷达数据多尺度滤波研究  

Multi-scale filtering of spaceborne lidar data based on improved DBSCAN

作　　者：钱政 毛志华 姚宝恒[1] QIAN Zheng;MAO Zhihua;YAO Baoheng(School of Oceanography,Shanghai JiaoTong University,Shanghai 201100,China;State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,China)

机构地区：[1]上海交通大学海洋学院,上海201100 [2]自然资源部第二海洋研究所卫星海洋环境动力学国家重点实验室,杭州310012

出　　处：《激光杂志》2024年第4期154-158,共5页Laser Journal

基　　金：国家重点研发计划支持项目(No.2016YFC1400901);上海交通大学“深蓝计划”基金资助项目(No.SL2022ZD206);自然资源部第二海洋研究所基本科研业务费专项资金资助项目(No.SL2302);国家自然科学基金资助项目(No.61991454)。

摘　　要：星载激光雷达数据滤波过程易受复杂背景、粗差点、噪声点等问题的干扰,导致滤波效果大幅度下降,所以研究基于改进DBSCAN的星载激光雷达数据多尺度滤波方法。采用改进DBSCAN算法对星载激光雷达数据做聚类处理,并标记噪声点,通过半球形邻域算法提取点云数据特征。根据提取到的点云数据特征构建规则格网,通过格网的多路径效应剔除点云数据中的粗差点与噪声点,完成星载激光雷达数据多尺度滤波。实验结果表明,所提方法的星载激光雷达数据多尺度滤波误差较低、滤波效果好,实际应用价值较高。The filtering process of spaceborne LiDAR data is susceptible to interference from complex backgrounds,gross errors,noise points,and other issues,resulting in a significant decrease in filtering effectiveness.Therefore,a multi-scale filtering method for spaceborne LiDAR data based on improved DBSCAN is studied.The improved DBSCAN algorithm is used to cluster spaceborne LiDAR data,label noise points,and extract point cloud data features using a hemispherical neighborhood algorithm.Based on the extracted point cloud data features,a regular grid is constructed,and the coarse points and noise points in the point cloud data are removed through the multipath effect of the grid,completing multi-scale filtering of spaceborne LiDAR data.The experimental results show that the proposed method has low multi-scale filtering error and good filtering effect for spaceborne LiDAR data,and has high practical application value.

关 键 词：改进DBSCAN 星载激光雷达 多尺度滤波 半球形邻域算法 规则格网 粗差点 噪声点 

分 类 号：TN249[电子电信—物理电子学]