摘要
针对目前三维探地雷达未充分挖掘三维空间信息,数据处理主要基于对二维切片图像进行分析解译的问题,本文提出了一种三维探地雷达数据体素化后基于离散点云的局部熵提取地下目标的方法。首先,将获取的三维探地雷达数据体素化为离散三维点云;然后,计算整个区域体素化后点云的局部熵,通过支持向量机(SVM)对土壤背景和地下目标从多个尺寸进行区分;最后,以城市道路地下环境为研究对象进行试验分析。试验结果表明,该方法提取地下目标的准确率高达84.2%,遗漏地下目标的漏测率低至9.8%。该方法准确有效,为三维探地雷达提取地下目标提供了一种新的方法。
A method for extracting underground target based on local entropy of discrete point clouds after voxelization of 3D ground penetrating radar(3D GPR)data is proposed to address the problem of insufficient exploration of 3D spatial information by 3D ground penetrating radar and the data processing mainly based on analysis and interpretation of 2D slice images.Firstly,the obtained 3D ground penetrating radar data was voxelized into discrete 3D point clouds.Then,the local entropy of the voxelized point cloud for the entire region were calculated.The soil background and underground targets were distinguished by classifying them from multiple dimensions through support vector machine(SVM).Finally,taking the underground environment of urban roads as the research object,it is used to conduct experimental analysis using measured data.The experimental results show that the accuracy of this method in extracting underground targets is as high as 84.2%,and the missed detection rate of underground targets is as low as 9.8%.This method is accurate and effective,providing a new approach for 3D ground penetrating radar to extract underground target.
作者
王文龙
胡庆武
张菊
赵鹏程
艾明耀
WANG Wenlong;HU Qingwu;ZHANG Ju;ZHAO Pengcheng;AI Mingyao(School of Remote Sensing,Wuhan University,Wuhan 430072,China;School of Architecture and Engineering,Wuhan City Polytechnic,Wuhan 430064,China)
出处
《测绘通报》
CSCD
北大核心
2024年第12期6-10,共5页
Bulletin of Surveying and Mapping
基金
武汉市知识创新专项基础研究项目(2022010801010431)。
关键词
三维探地雷达
地下目标提取
局部熵
体素化
3D ground penetrating radar
underground target extraction
local entropy
voxelization
