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首页> 外文期刊>Journal of Sensors >Automated Coregistration of Multisensor Orthophotos Generated from Unmanned Aerial Vehicle Platforms
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Automated Coregistration of Multisensor Orthophotos Generated from Unmanned Aerial Vehicle Platforms

机译:从无人机飞行器平台产生的多传感器矫形器的自动核心核算

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Image coregistration is a key preprocessing step to ensure the effective application of very-high-resolution (VHR) orthophotos generated from multisensor images acquired from unmanned aerial vehicle (UAV) platforms. The most accurate method to align an orthophoto is the installation of air-photo targets at a test site prior to flight image acquisition, and these targets were used as ground control points (GCPs) for georeferencing and georectification. However, there are time and cost limitations related to installing the targets and conducting field surveys on the targets during every flight. To address this problem, this paper presents an automated coregistration approach for orthophotos generated from VHR images acquired from multisensors mounted on UAV platforms. Spatial information from the orthophotos, provided by the global navigation satellite system (GNSS) at each image’s acquisition time, is used as ancillary information for phase correlation-based coregistration. A transformation function between the multisensor orthophotos is then estimated based on conjugate points (CPs), which are locally extracted over orthophotos using the phase correlation approach. Two multisensor datasets are constructed to evaluate the proposed approach. These visual and quantitative evaluations confirm the superiority of the proposed method.
机译:图像核心标制是一种关键的预处理步骤,以确保从无人驾驶车辆(UAV)平台获取的多传感器图像产生的非常高分辨率(VHR)官能体的有效应用。对齐的最准确的方法是在飞行图像采集之前在测试部位安装空气 - 照片目标,并且这些目标被用作地理处理和地球化的地面控制点(GCPS)。但是,有时间和成本限制与安装目标和在每次航班期间对目标进行现场调查。为了解决这个问题,本文提出了一种自动研究从安装在UAV平台上的多传感器获取的VHR图像中生成的正交核心核心试卷方法。由每个图像的获取时间的全球导航卫星系统(GNSS)提供的来自正轨光盘的空间信息用作基于相位相关的核心转化仪的辅助信息。然后基于使用相位相关方法在缀合物点(CPS)上局部提取的缀合物点(CPS)之间的变换函数。构建两个多传感器数据集以评估所提出的方法。这些视觉和定量评估证实了所提出的方法的优越性。

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