摘要
通过三维激光扫描仪获取的点云数据具有大体量、高冗余且非结构化的特点。在使用传统滤波方法进行去噪时,不能兼顾滤波效果与保留细节特征,会造成精度丢失。本文针对以上问题,将噪声划分为远距离的大尺度噪声以及近距离的小尺度噪声,研究基于统计分析结合图像引导滤波的多尺度点云滤波去噪方法。经过实验验证,本文算法可以在不丢失点云细节特征的前提下,实现点云数据的优化以及精简。
The point cloud data obtained by 3D laser scanner have the characteristics of large amount,high redundancy and unstructured.When the traditional filtering method is used for denoising,it cannot take into account the filtering effect and retain the detail characteristics,which will cause the loss of accuracy.Aiming at the above problems,this paper divided the noise into long-distance large-scale noise and short-distance small-scale noise,and studied the multi-scale point cloud filtering denoising method based on statistical analysis and image guided filtering.After experimental verification,the algorithm in this paper could realize the optimization and simplification of point cloud data without losing the detailed characteristics of point cloud.
作者
刘翔宇
宋羽
LIU Xiangyu;SONG Yu(College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao Shandong 266590,China;Jinan Geotechnical Investigation and Surveying Institute,Jinan Shandong 250013,China)
出处
《北京测绘》
2022年第11期1486-1489,共4页
Beijing Surveying and Mapping
关键词
三维激光扫描
点云去噪
统计分析
半径滤波
双边滤波
three dimensional(3D)laser scanning
point cloud denoising
statistical analysis
radius filtering
bilateral filtering
