中国激光, 2016, 43 (5): 0514002, 网络出版: 2016-05-04   

融合航空影像和LIDAR点云的建筑物探测及轮廓提取 下载: 1276次

Buildings Detection and Contour Extraction by the Fusion of Aerial Images and LIDAR Point Cloud
作者单位
1 同济大学测绘与地理信息学院, 上海 200092
2 上海船舶研究设计院, 上海 201203
摘要
通过分析机载雷达(LIDAR)点云数据与航空影像数据特点,提出了融合机载LIDAR点云和航空影像的建筑物轮廓探测方法。分别提取机载点云和航空影像中的部分建筑轮廓线,将轮廓线拟合成直线段的建筑物轮廓边,并以两相邻且垂直的轮廓边相交得到建筑的角点,根据建筑物的同名角点实现机载点云和航空影像的配准融合;将航空影像的光谱信息赋予机载点云,并将光谱信息作为特征向量进行聚类,分离出植被和树木等地物,利用高程信息从光谱信息相似的地面道路和建筑物中分离出建筑物,提取建筑物的轮廓边,完成建筑物轮廓的探测。实验结果表明,利用该方法进行建筑物点云的分类正确率可达97.96%,轮廓边的提取精度可达0.21 m,能够有效的实现建筑物轮廓的探测。
Abstract
The method of extracting building boundaries based on the fusion of airborne radar (LIDAR) point cloud and aerial images is proposed by analyzing the feature of airborne LIDAR point cloud data and aerial images data. The contour line of buildings are extracted from both the point cloud and the aerial images. The contour line is fitted to lines of the building boundaries. The building vertexes are derived from two adjacent and vertical boundaries. The registration fusion of airborne point cloud and aerial images is achieved according to the correspondence vertexes of building. The point clouds get the spectral information of aerial images, which is used as a feature vector of clustering analysis to extract plants, trees and other objects. The height information is used to extract building from the buildings and roads which have similar spectral information, and the accurate boundaries of buildings are extracted and the detection of the boundaries of building is achieved. Experimental results indicate that the accuracy of point cloud classification can reach 97.96%, and the precision of the extraction of building boundaries can be up to 0.21 m, which ensures an effective way of detecting building boundaries.

程效军, 程小龙, 胡敏捷, 郭王, 张立朔. 融合航空影像和LIDAR点云的建筑物探测及轮廓提取[J]. 中国激光, 2016, 43(5): 0514002. Cheng Xiaojun, Cheng Xiaolong, Hu Minjie, Guo Wang, Zhang Lishuo. Buildings Detection and Contour Extraction by the Fusion of Aerial Images and LIDAR Point Cloud[J]. Chinese Journal of Lasers, 2016, 43(5): 0514002.

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