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自适应局部空谱一致下的机载LiDAR数据建筑物提取算法

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现有研究均将建筑物激光反射强度的全局统计特性用于辅助机载激光雷达数据的建筑物提取,但是这类方法无法满足大尺度复杂城区场景下光谱迥异建筑物完备、准确提取的需求.为此,本文提出一种自适应局部空谱一致下的机载LiDAR数据建筑物提取方法.该方法首先将原始机载LiDAR数据转换为LiDAR 3D影像.然后,依据建筑物高程跳变和边缘局部接近直线特性选取种子体素,进而依据单体建筑示出的空间连续性及光谱一致性将与种子体素空谱一致的连通分量标记为建筑物屋顶.其中,单体建筑的光谱一致性由统计空间连通的种子体素的强度特性给出.最后,结合建筑屋顶对立面的空间约束以及立面的局部强度一致性约束提取建筑物立面.该方法通过自适应于各建筑单体光谱的设计解决了不符合光谱全局统计特性的建筑物的准确提取问题,提升了点云光谱信息的使用价值,并由此拓宽了点云光谱信息的应用场景.选用国际摄影测量与遥感协会提供,不同复杂程度的3组城区场景实测机载LiDAR数据测试本文方法的可行性和有效性.试验结果表明:可实现不同复杂程度场景下的建筑物提取;建筑物提取结果的平均完整率、正确率及质量分别为99.0%、98.0%、96.8%,明显优于传统的利用光谱全局统计特性的建筑物提取方法.
An algorithm for building extraction from airborne LiDAR data under adaptive local spatial-spectral consistency
All the existing studies use the global statistical characteristics of laser reflection intensity of buildings to aid the extraction of buildings from airborne LiDAR data,but this solution cannot meet the needs of comprehensive and accurate extraction of buildings with different spectra in large-scale complex urban scenes.Therefore,a building extraction method from airborne LiDAR data based on adaptive local spatial-spectral consistency is developed.The proposed method first converts raw airborne LiDAR data into 3D image.Then,the seeds are selected according to the characteristics of building elevation jump and edge approaching straight line.Subsequently,the connected components that are spatially and spectrally consistent with the seedsare labeled as the building roof,in which the spectral consistency is given by the statistical intensity properties of an indi-vidual building.Finally,the building facade is extracted by combining the spatial constraint of the extracted building roof and the local intensity consistency constraints.This method solves the problem of accurate extraction of buildings that do not con-form to the global statistical characteristic of the spectrum by self-adapting to the local spectrum of each individual building,improves the use value of point cloud spectral information,and thus broadens the application scenarios of point cloud spectral information.Three airborne LiDAR datasets of urban scene with different complexities provided by International Association for Photogrammetry and Remote Sensing are used to test the feasibility and effectiveness of the proposed method.The experi-mental results show that the proposed method can excellently extract buildings in scenes with different complexities.The aver-age completeness,accuracy and quality of the building extraction results are 99.0%,98.0%and 96.8%,respectively,which are obviously better than the traditional building extraction method using the global statistical properties of the spectrum.

airborne LiDARbuilding extractionspatial-spectral consistencypoint cloudglobal statistical characteristic

王丽英、张康丽、李鑫奥、有泽、丰勇

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辽宁工程技术大学测绘与地理科学学院,辽宁阜新 123000

辽宁省自然资源厅地理信息管理处,辽宁沈阳 110032

机载激光雷达 建筑物提取 空谱一致 点云 全局统计特性

2024

测绘学报
中国测绘学会

测绘学报

CSTPCD北大核心
影响因子:1.602
ISSN:1001-1595
年,卷(期):2024.53(12)