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MULTI-SCALE MATCHING FOR THE AUTOMATIC LOCATION OF CONTROL POINTS IN LARGE SCALE AERIAL IMAGES USING TERRESTRIAL SCENES

机译:使用地面场景的大规模空中图像中控制点自动定位多尺度匹配

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A technique to automatically locate Ground Control Points (GCPs) in large aerial images is presented considering the availability of low accuracy direct georeferencing data. The approach is based on image chips of GCPs extracted from vertical terrestrial images. A strategy combining image matching techniques was implemented to select correct matches. These matches were used to define a 2D transformation with which the GCP is projected close to its correct position, reducing the search space in the aerial image. Area-based matching with some refinements is used to locate GCPs with sub-pixel precision. Experiments were performed with multi-scale images and assessed with a bundle block adjustment simulating an indirect sensor orientation. The accuracy analysis was accomplished based on discrepancies obtained from GCPs and check points. The results were better than interactive measurements and a planimetric accuracy of 1/5 of the Ground Sample Distance (GSD) for the check points was achieved.
机译:考虑到了低精度直接地理移植数据的可用性,提出了一种在大型航天图像中自动定位地面控制点(GCP)的技术。该方法基于从垂直地面图像中提取的GCP的图像芯片。实现了一种结合图像匹配技术的策略来选择正确的匹配。这些匹配用于定义2D变换,其中GCP突出接近其正确位置,减少了航空图像中的搜索空间。基于区域的匹配与一些改进用于定位具有子像素精度的GCP。用多尺度图像进行实验,并用模拟间接传感器方向的束块调整评估。基于从GCPS获得的差异和检查点完成的精度分析。结果比交互式测量更好,实现了检查点的1/5的平面精度,检查点的一个接地样品距离(GSD)。

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