This paper presents an automatic procedure for the geometric corrections of very-high resolution (VHR) optical panchromatic satellite images. The procedure is composed of three steps: an automatic ground control point (GCP) extraction algorithm that matches the linear features that were extracted from the satellite image and reference data; a geometric model that applies a rational function model; and, the orthorectification procedure. Accurate geometric corrections can only be achieved if GCPs are employed to precisely correct the geometric biases of images. Due to the high resolution and the varied acquisition geometry of images, we propose a fast, segmentation based method for feature extraction. The research focuses on densely populated urban areas, which are very challenging in terms of feature extraction and matching. The proposed algorithm is capable of achieving results with a root mean square error of approximately one pixel or better, on a test set of 14 panchromatic Pléiades images. The procedure is robust and it performs well in urban areas, even for images with high off-nadir angles.
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机译：本文介绍了高分辨率（VHR）光学平面卫星图像的几何校正的自动过程。该过程由三个步骤组成：自动接地控制点（GCP）提取算法与从卫星图像和参考数据中提取的线性功能匹配;一种应用Rational Function Model的几何模型;并且，矫正程序。只有使用GCPS精确地校正图像的几何偏差，才能实现精确的几何校正。由于图像的高分辨率和变化的图像几何形状，我们提出了一种快速，分段的特征提取方法。该研究重点介绍了人口密集的城市地区，这在特征提取和匹配方面非常具有挑战性。所提出的算法能够在14个PanchromaticPléiades图像的测试组上实现具有大约一个像素的根均方误差的结果。该程序很健壮，它在城市地区表现良好，即使对于具有高偏离Nadir角度的图像也是如此。
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