摘要
点云降噪对激光雷达成像系统的精度至关重要。为了降低由接收器、多径效应、外部干扰和大气扰动引起的噪声,采用基于遗传算法的半径滤波进行降噪,通过遗传算法优化了半径滤波的关键参数(过滤半径和近邻阈值)。结果表明,在简单与复杂场景中,该算法保持了去噪精度和点保留率,同时提高了噪声召回率;复杂环境下噪声召回率比半径滤波提高了约21%,比统计滤波提升了约16%。该方法为激光雷达数据的处理提供了一种新颖有效的解决方案,对于提高激光雷达成像质量、提升数据处理效率以及自动化分析具有较为重要的应用价值。
Point cloud noise reduction is crucial to the accuracy of light detection and ranging(LiDAR)imaging systems.In order to reduce the noise caused by receiver,multipath effect,external interference and atmospheric disturbances,a radius filtering method based on genetic algorithm was used for noise reduction,which optimized the key parameters of radius filtering(filtering radius and nearest-neighbor thresholds)by genetic algorithm.Validation in simple and complex scenes show that,the algorithm maintains denoising accuracy and point retention in simple scenes while slightly improving noise recall.The noise recall in complex scenes is improved by about 21%over traditional radius filtering and about 16%over statistical filtering,which is useful for point cloud radius filtering.The radius filtering based on genetic algorithm provides a novel and effective method for LiDAR data processing,which is valuable for improving the quality of LiDAR imaging.
作者
赵哲
周维龙
龙欢
周红
梁登辉
柳骏涛
李小宝
ZHAO Zhe;ZHOU Weilong;LONG Huan;ZHOU Hong;LIANG Denghui;LIU Juntao;LI Xiaobao(College of Railway Transportation,Hunan University of Technology,Zhuzhou 412007,China;College of Electrical and Information Engineering,Hunan University of Technology,Zhuzhou 412007,China)
出处
《激光技术》
北大核心
2025年第2期210-215,共6页
Laser Technology
基金
湖南省教育厅优秀青年基金资助项目(18B305)。
关键词
成像系统
降噪
遗传算法
点云
imaging system
noise reduction
genetic algorithm
point cloud
