| 一种地面激光雷达点云与纹理影像稳健配准方法 |
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| 引用本文： | 王晏民,胡春梅.一种地面激光雷达点云与纹理影像稳健配准方法[J].测绘学报,2012,41(2):266-272. |
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| 作者姓名： | 王晏民 胡春梅 |
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| 作者单位： | 1. 北京建筑工程学院测绘系;2. 武汉大学; |
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| 基金项目： | 北京市属高等学校人才强教深化计划“高层次人才资助计划”，京市自然科学基金重点项目B类 |
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| 摘 要： | 为了使地面激光雷达点云得到真实和高分辨率纹理，需要对目标进行全方位的拍照。这时点云和影像的配准会出现大角度的问题。同时，由于控制点选点误差、仪器误差等，配准精度往往不能满足要求。针对以上问题，本文提出一种稳健的配准方法。首先，应用重心化的空间相似变换模型和正交旋转矩阵与反对称矩阵的关系推导解算配准参数角元素的模型。将配准结果当作初始值。然后，应用一种基于共线方程的改进丹麦法选权迭代法进行降权精确配准，确定配准参数的精确值。试验表明，本文方法稳定性强、配准精度高，适合任意角度影像与点云的高精度配准。
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| 关 键 词： | 地面激光雷达 大角度影像 影像配准 丹麦法选权迭代 |
| 收稿时间： | 2011-10-10 |
| 修稿时间： | 2011-12-11 |
A Robust Registration Method for Terrestrial LiDAR Point Clouds and Texture Image |
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| WANG Yanmin,HU Chunmei.A Robust Registration Method for Terrestrial LiDAR Point Clouds and Texture Image[J].Acta Geodaetica et Cartographica Sinica,2012,41(2):266-272. |
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| Authors: | WANG Yanmin HU Chunmei |
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| Institution: | 1.State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;2.Key Laboratory for Urban Geomatics of National Administration of Surveying,Mapping and Geoinformation,Beijing University of Civil Engineering and Architecture,Beijing 100044,China |
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| Abstract: | In order to get true and high resolution texture for terrestrial LiDAR point clouds,the photo should be taken to all directions.This will cause the large angle problem for the registration of point clouds and the texture image.Meanwhile,the error from control points and scanner also creates the low registration accuracy.A robust registration method is proposed to solve these problems.First,orientation element model of registration parameter is derived by the barycenter model of the space similarity transformation,normal rotation matrix and the antisymmetric matrix.The registration result is treated as initial value.Then,the high accuracy registration parameters are obtained by improved Danish iteration method with variable weights based on collinearity equation.Experiment shows that the new method is robust and accurate for the registration of any angle image and point clouds. |
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| Keywords: | territorial LiDAR large angle image image registration Danish iteration method with variable weights |
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