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城区机载LiDAR数据与航空影像的自动配准
引用本文:张永军,熊小东,沈翔. 城区机载LiDAR数据与航空影像的自动配准[J]. 遥感学报, 2012, 16(3): 579-595
作者姓名:张永军  熊小东  沈翔
作者单位:武汉大学 遥感信息工程学院, 湖北 武汉 430079;武汉大学 遥感信息工程学院, 湖北 武汉 430079;武汉大学 遥感信息工程学院, 湖北 武汉 430079
基金项目:国家重点基础研究发展计划(973计划)(编号:2012CB719904);国家自然科学基金(编号:41171292,41071233)
摘    要:为解决机载LiDAR数据与航空影像集成应用中二者的配准问题,提出了一种机载LiDAR数据与航空影像配准的方法。首先,直接在LiDAR点云中提取建筑物3维轮廓线,通过将轮廓线规则化得到由两条相互垂直的直线段组成的建筑物角特征,并在航空影像上提取直线特征;然后,根据影像初始外方位元素将建筑物角特征投影到航空影像上,并采用一定的相似性测度在影像上寻找同名的影像角特征;最后,将角特征的角点当作控制点,利用传统的摄影测量光束法区域网平差解求影像新的外方位元素。解算过程中采用循环迭代策略。本方法的主要特点是,直接从LiDAR点云中提取线特征,避免了常规方法从距离图(或强度图)中提取线特征所产生的内插误差。通过与现有基于点云强度图的配准方法的对比实验表明,在低精度初始外方位元素的辅助下,本文方法能够达到较高的配准精度。

关 键 词:机载LiDAR  航空影像  配准  线特征  角特征
收稿时间:2011-04-01
修稿时间:2011-07-04

Automatic registration of urban aerial imagery with airborne LiDAR data
ZHANG Yongjun,XIONG Xiaodong and SHEN Xiang. Automatic registration of urban aerial imagery with airborne LiDAR data[J]. Journal of Remote Sensing, 2012, 16(3): 579-595
Authors:ZHANG Yongjun  XIONG Xiaodong  SHEN Xiang
Affiliation:School of Remote Sensing and Information Engineering of Wuhan University, Wuhan 430079, China;School of Remote Sensing and Information Engineering of Wuhan University, Wuhan 430079, China;School of Remote Sensing and Information Engineering of Wuhan University, Wuhan 430079, China
Abstract:This paper presents a new algorithm for the automatic registration of airborne LiDAR data with aerial images using building corner features as registration primitives. First, three-dimensional building outlines are directly extracted from LiDAR points and building corner features which consist of two orthogonal straight lines are obtained by the regularization of threedimensional building outlines. Straight lines are also extracted from every aerial image. Second, the building corner features are projected onto aerial images and corresponding image corner features are determined using the similarity measures. Lastly, the exterior orientation parameters are refined by bundle adjustment using the corner points of corner features as control points. Iteration strategy is adopted to obtain optimal results. The main advantage of the proposed algorithm is that the three-dimensional building outlines are extracted directly from LiDAR points without transforming LiDAR points into range image or intensity image, and therefore there are no interpolation errors. The experimental results show that the proposed algorithm can obtain more accurate results in comparison with the registration method based on LiDAR intensity image.
Keywords:airborne LiDAR  aerial imagery  registration  line  corner
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