首页|基于CSF和CANUPO的建筑屋顶和立面点云提取

基于CSF和CANUPO的建筑屋顶和立面点云提取

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倾斜航空影像具有高重叠率、建筑物立面可见、遮挡少的特点,能够有效地提取建筑信息,本研究将对倾斜航空影像进行处理,生成密集点云,通过布料模拟算法(CSF)过滤出地面点和非地面点,并对非地面点进行去噪处理.利用CANUPO算法将非地面点分类为建筑、植被和其他.然后对建筑点进行法线计算,根据法线结果提取建筑的屋顶点和立面点,提取精度能达到人工提取的80%左右,这种方法能够简单有效地为用户提供给定区域建筑屋顶和立面的初步信息.
Point Cloud Extraction of Building Roof and Facade Based on CSF and CANUPO
Oblique aerial images have the characteristics of high overlap rate,visible building facades and less occlusion,which can effec-tively extract building information.In this study,tilting aerial images will be processed to generate dense point clouds,and ground points and non-ground points will be filtered out by cloth simulation algorithm(CSF),and non-ground points will be de-noised.The CANUPO algo-rithm is used to classify non-ground points into buildings,vegetation and others.Then the normal calculation of the building points,according to the normal results to extract the building roof points and facade points,the extraction accuracy can reach about 80%of manual extraction,this method can simply and effectively provide users with the initial information of the building roof and facade in a given area.

oblique aerial imagedense point cloudcloth simulation(CSF)CANUPOnormal estimation

杜文俊、刘小军、赵云景、龚绪才

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云南省基础测绘技术中心,云南 昆明 650034

倾斜航空影像 密集点云 布料模拟(CSF) CANUPO 法线计算

2024

城市勘测
中国城市规划协会 武汉市测绘研究院

城市勘测

影响因子:0.488
ISSN:1672-8262
年,卷(期):2024.(6)