城区机载激光雷达点云数据与航空影像的多尺度配准方法

提出了一种激光雷达(LiDAR)点云数据和航空影像的多尺度配准方法. 该方法采用渐进式的配准策略,利用面形态学的方法构建尺度空间. 配准过程分为两部分:在大尺度下利用面片特征进行配准;在小尺度下利用直线特征进行配准. 渐进式的配准策略简化搜索匹配的直线特征的过程,提高了自动化程度,构建基于面形态学的尺度空间提高了配准元的提取精度. 最后,通过实验验证了方法的可行性. 

Multi-Scale Registration of LiDAR Data and Aerial Image

A multi-scale registration method was presented for aerial image and light detection and ranging (LiDAR) data. Multi-scale registration refers to a "from coarse to fine" and progressive registration strategy based on scale-space theory. Area morphology was used to build the scale-space. The methodology includes two parts: first, registration in coarse scale with surface patch and second, registration in fine scale with linear feature. In this proposed method, the search for matched lines was simplified as a result of progressive registration strategy. The automaticity was improved. Besides, the area morphological scale-space was used to improve the accuracy of extraction of the registration primitives. This method was verified with experiment.