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Automatic Geometric Processing for Very High Resolution Optical Satellite Data Based on Vector Roads and Orthophotos

机译:基于矢量路和正射影像的超高分辨率光学卫星数据的自动几何处理

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In response to the increasing need for fast satellite image processing SPACE-SI developed STORM—a fully automatic image processing chain that performs all processing steps from the input optical images to web-delivered map-ready products for various sensors. This paper focuses on the automatic geometric corrections module and its adaptation to very high resolution (VHR) multispectral images. In the automatic ground control points (GCPs) extraction sub-module a two-step algorithm that utilizes vector roads as a reference layer and delivers GCPs for high resolution RapidEye images with near pixel accuracy was initially implemented. Super-fine positioning of individual GCPs onto an aerial orthophoto was introduced for VHR images. The enhanced algorithm is capable of achieving accuracy of approximately 1.5 pixels on WorldView-2 data. In the case of RapidEye images the accuracies of the physical sensor model reach sub-pixel values at independent check points. When compared to the reference national aerial orthophoto the accuracies of WorldView-2 orthoimages automatically produced with the rational function model reach near-pixel values. On a heterogeneous set of 41 RapidEye images the rate of automatic processing reached 97.6%. Image processing times remained under one hour for standard-size images of both sensor types.
机译:为响应对快速卫星图像处理的不断增长的需求,SPACE-SI开发了STORM,这是一种全自动图像处理链,可以执行从输入光学图像到网络交付的各种传感器的地图就绪产品的所有处理步骤。本文重点介绍自动几何校正模块及其对超高分辨率(VHR)多光谱图像的适应性。在自动地面控制点(GCP)提取子模块中,最初实现了两步算法,该算法利用矢量路作为参考层,并以接近像素的精度为高分辨率RapidEye图像提供GCP。对于VHR图像,引入了将单个GCP超精细定位到航空正射影像上的功能。增强的算法能够在WorldView-2数据上实现约1.5个像素的精度。对于RapidEye图像,物理传感器模型的精度在独立的检查点达到了亚像素值。与参考国家航空正射影像相比,使用有理函数模型自动生成的WorldView-2正射影像的精度达到了近像素值。在一组41张RapidEye图像的异类上,自动处理率达到97.6%。对于两种传感器类型的标准尺寸图像,图像处理时间都保持在一小时以下。

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