基于遗传算法的统计滤波点云降噪算法  

Statistical Filtering Point Cloud Denoising Algorithm Based on Genetic Algorithm

作　　者：艾小童 Ai Xiaotong(China Railway SIYUAN Survey and Design Group Co.,Ltd,Wuhan 430063)

机构地区：[1]中铁第四勘察设计院集团有限公司勘察院,武汉430063

出　　处：《铁道勘测与设计》2025年第1期19-23,共5页Railway Survey and Design

摘　　要：随着三维传感技术的发展,点云数据在地形测量和其他应用中的使用越来越广泛。然而,由于受气象条件、地形环境及设备等因素影响,采集到的点云数据中含有大量的噪点,致使点云数据的精度下降。本文提出了一种基于遗传算法优化统计滤波的点云噪点分类与去除方法,该方法可以在不同地形条件下自适应地选择最佳参数,有效提高点云去噪的效率和精度,保留原始地物特征。With the development of 3D sensing technology,the use of point cloud data in terrain measurement and other applications is becoming increasingly widespread.However,due to factors such as meteorological conditions,terrain environment,and equipment,the collected point cloud data contains a large amount of noise,resulting in a decrease in the accuracy of the point cloud data.This article proposes a point cloud noise classification and removal method based on genetic algorithm optimized statistical filtering.This method can adaptively select the best parameters under different terrain conditions,effectively improving the efficiency and accuracy of point cloud denoising while preserving the original land features.

关 键 词：点云数据 噪点去除 遗传算法 统计滤波 激光雷达 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]