Linear-Feature-Constrained Registration of LiDAR Point Cloud via Quaternion
-
摘要: 针对参数模型的局限性,提出了利用半参数模型的卫星影像定位方法。利用SPOT-5、IKONOS影像进行实验,分别采用严格成像模型和有理函数模型进行立体定位,实验结果表明:无控制点的情况下,采用半参数模型进行立体定位,SPOT-5的估计结果普遍优于参数估计,IKONOS的平面点位误差较小,其平面点位的半参数模型估计精度与参数模型基本相当,而高程的半参数模型估计精度要优于参数模型。Abstract: Considering the large amount of computation & low accuracy of extracted point-like features are the two main disadvantages of traditional point-to-point based registration methods which is designed for LiDAR point cloud,and the accuracy of registration results is seriously decreased by the linearization procedure of traditional 7-parameter based transformation approaches,a new registration approach is designed to overcome above disadvantages,which selects linear features as registration primitives,and uses quaternion to represent rotation matrix.Similarity measure of the linear-feature-constrained 3D transformation procedure is presented,and the formulation of registration procedure is exactly deduced.Besides,the detailed procedure of how to calculate rotation,translation & scale is also presented.Experiments show that the presented approach is efficient & effective.More importantly,by using quaternion to represent rotation matrix,the new presented approach avoids the decrease of accuracy,meanwhile,due to the characteristic of quaternion,it also needs few calculation resources compared to traditional registration methods.
-
-
[1] 袁修孝,张过.缺少控制点的卫星遥感对地目标定位[J].武汉大学学报?信息科学版,2003,28(5):505-509[2]童小华,刘世杰,叶勤.基于有理函数模型的Quick-Bird立体定位精度分析[J].同济大学学报(自然科学版),2009,37(4):555-559
计量
- 文章访问数: 1165
- HTML全文浏览量: 53
- PDF下载量: 414
下载:
