摘要
针对机载点云数据建筑物提取困难问题,提出融光谱信息的机载点云建筑物提取方法。首先,将激光雷达扫描的点云数据转换为强度影像与遥感影像配准,融合得到具有光谱信息的点云数据;然后,利用可见光差异植被指数对点云建筑物提取算法进行优化,从而获取更精确的建筑物顶部数据;最后,以飞马D2000的点云数据为例,提取建筑点云。结果表明,该方法能有效分离出建筑物。
Aiming at the difficulty of building extraction from airborne point cloud data,an airborne point cloud building extraction method integrating spectral information is proposed.Firstly,the point cloud data acquired by LiDAR is transformed into intensity images and registered with remote sensing images,and the point cloud data with spectral information is obtained by image fusion.Then,the visible light difference vegetation index is used to optimize the point cloud building extraction algorithm,so as to obtain more accurate building top data.Finally,taking Pegasus D2000 point cloud data as an example,the building point cloud is extracted.The results show that this method can effectively separate buildings.
作者
何永钟
HE Yongzhong(Guangdong Lianhejindi Real Estate Appraisal Survey and Design Co.,Ltd.,Shaoguan 512026,China)
出处
《测绘与空间地理信息》
2023年第7期181-183,共3页
Geomatics & Spatial Information Technology
关键词
机载点云
光谱信息
建筑物提取
可见光植被指数
airborne point cloud
spectral information
building extraction
visible vegetation index
