期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B3
页码：1043-1048
出版社：Copernicus Publications
摘要：At present, the calibration of airborne laser scanner data relies on the estimation of the position and attitude of the aircraft during the acquisition using GPS and INS systems, but also on the estimation of some other parameters: time bias, scan angle offset, etc, which usually requires the acquisition of extra data over known features: along and across the airport runway, over an horizontal building edge, etc. The operator need then to identify within the cloud of 3D points the position of these known features. The aim of this paper is to propose a tool for the automated registration of airborne laser scanner data with one aerial image over urban areas. The method makes use of the intrinsic rigidity of the aerial image: the registration is performed by optimizing the 3D reconstruction of the scene calculated with the aerial image and the laser points. On the assumption that urban areas are mainly composed of planar surfaces, a segmentation algorithm generates a partition of the aerial image and a robust technique estimates a 3D plane for each region. The quality of the registration is calculated according to the global number of outliers remaining after the robust estimation. Experimental results show the convexity of this registration estimator for some low frequency deformations: 3D translations and rotations, and also curvature along and across the .ying direction. The system then uses a Nelder-Mead simplex algorithm to calculate a precise registration of both data sets
