测绘科学技术学报2017，Vol.34Issue(5)：491-495,5.DOI:10.3969/j.issn.1673-6338.2017.05.011
深度图像分割的城市区域倾斜影像密集匹配点云滤波算法
Filtering Urban Point Cloud from Dense Image Matching Based on Depth Image Segmentation
摘要
Abstract
Oblique photogrammetry is a new and rapidly developing technique which is widely used in many fields,but the study of dense matching point cloud processing technology is less.The typical point cloud filtering algorithms for laser scanning data are not suitable for dense matching point cloud because of the inhomogeneous point distribution and rough surface in dense matching data.In the light of the characteristics of dense point cloud,a fast point cloud filtering method is proposed.Firstly,depth image is generated from elevation data where the disconnected area is extracted using spatial features.Then,the depth image is segmented by region growing using multiple global seeds.Experimental results show that this algorithm is effective and efficient in filtering dense matching point cloud,especially in solving the problem that the bottom edges of the objects are not clear and the problem that region growing cannot perform well in the disconnected area in the buildings.关键词
倾斜影像/密集匹配点云/深度图像/区域生长/滤波Key words
oblique images/dense matching point cloud/depth image/region growing/filtering分类
天文与地球科学引用本文复制引用
季虹良,戴晨光,张鑫禄,莫德林,仇多兵..深度图像分割的城市区域倾斜影像密集匹配点云滤波算法[J].测绘科学技术学报,2017,34(5):491-495,5.基金项目
对地观测技术国家测绘地理信息局重点实验室开放基金项目(K201508). （K201508）
