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Method for automatic georeferencing aerial remote sensing (RS) images from an unmanned aerial vehicle (UAV) platform

机译:从无人飞行器(UAV)平台自动地理配准航空遥感图像的方法

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Before an aerial image can be used to support a site-specific application it is essential to perform the geometric corrections and geocoding. This research discusses the development of an automatic aerial image georeferencing method for an unmanned aerial vehicle (UAV) image data acquisition platform that does not require use of ground control points (GCP). An onboard navigation system is capable of providing continuous estimates of the position and attitude of the UAV. Based on a navigation data and a camera lens distortion model, the image collected by an onboard multispectral camera can be automatically georeferenced. When compared with 16 presurveyed ground reference points, image automatic georeferenced results indicated that position errors were less than 90 cm. A large field mosaic image can be generated according to the individual image georeferenced information. A 56.9 cm mosaic error was achieved. This accuracy is considered sufficient for most of the intended precision agriculture applications
机译:在航空影像可以用于支持特定地点的应用之前,必须执行几何校正和地理编码。这项研究讨论了自动航空影像地理配准方法的发展,该方法适用于不需要使用地面控制点(GCP)的无人机(UAV)影像数据采集平台。机载导航系统能够连续评估无人机的位置和姿态。基于导航数据和相机镜头畸变模型,可以自动对车载多光谱相机收集的图像进行地理参考。与16个预先测量的地面参考点相比,图像自动地理参考结果表明位置误差小于90 cm。可以根据各个图像的地理参考信息生成大视场马赛克图像。达到了56.9厘米的镶嵌误差。该精度被认为足以满足大多数预期的精准农业应用

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