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Automatic co-registration of satellite imagery and LiDAR data using local Mutual Information

机译:使用本地相互信息自动共同注册卫星图像和LiDAR数据

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Automatic co-registration is a basic step in multi-sensor data fusion for remote sensing applications. The effectiveness of Mutual Information (MI) as a similarity measure for multi-sensor image registration has previously been reported for medical and remote sensing applications. In this paper, a new intensity-based approach built on local MI principles is presented. The approach decreases the complexity of higher dimension optimization by measuring local MI on well-distributed tie points. In addition, the reliability of registration is improved due to utilization of redundant observations of similarity. The performance of the proposed method for the registration of WorldView2 satellite imagery with LiDAR elevation and intensity data has been experimentally evaluated and the results obtained are presented.
机译:自动共注册是用于遥感应用的多传感器数据融合的基本步骤。互助信息(MI)作为多传感器图像配准的相似性度量的有效性先前已被报道用于医疗和遥感应用。在本文中,提出了一种基于局部MI原理的基于强度的新方法。该方法通过测量分布均匀的联络点上的局部MI降低了高维优化的复杂性。另外,由于利用了相似性的冗余观察,提高了注册的可靠性。实验评估了所提出的用LiDAR仰角和强度数据对WorldView2卫星图像进行配准的方法的性能,并介绍了获得的结果。

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