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Advanced Geosynchronous Studies Imager (AGSI): image navigation and registration (INR) system

机译:先进的地球同步研究成像仪(AGSI):图像导航和配准(INR)系统

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Abstract: Accurate and automatic image navigation and registration (INR) of remotely sensed data will be an essential element of future NASA satellite observation systems. INR describes the process by which geographic locations of the image pixels are computed and successive images from the same sensor are aligned to each other over time. For sensors such as the Advanced Geosynchronous Studies Imager (AGSI), a number of distortions prevent successive images from being perfectly registered to each other or to a fixed coordinate system. Most distortions in such images are the combined effects of sensor operation, satellite orbit and attitude, and atmospheric and terrain effects. These distortions are usually corrected by two methods; systematic correction, which relies on image acquisition models taking into account satellite orbit and attitude, sensor characteristics, platform/sensor relationship, and terrain models, and precision correction, which is feature-based, starting from the result of the systematic correction, and refining the geolocation or relative registration to subpixel precision. This paper describes the AGSI INR requirements and concepts, the image navigation model, a description of some potential precision correction methods utilizing edge and wavelet features, and a study of all the different error sources. The issues of swath-to-swath correlation and channel-to- channel coregistration are also described. !19
机译:摘要:遥感数据的准确,自动的图像导航和配准(INR)将是未来NASA卫星观测系统的重要组成部分。 INR描述了这样的过程,通过该过程可以计算图像像素的地理位置,并随着时间的推移将来自同一传感器的连续图像彼此对齐。对于诸如高级地球同步研究成像仪(AGSI)之类的传感器,许多失真会阻止连续的图像彼此之间或与固定坐标系之间的完美配准。此类图像中的大多数失真是传感器操作,卫星轨道和姿态以及大气和地形影响的综合影响。这些失真通常可以通过两种方法进行校正:系统校正,它依赖于图像采集模型,该模型考虑了卫星轨道和姿态,传感器特性,平台/传感器关系和地形模型,以及基于系统校正和精炼的基于特征的精度校正地理位置或相对配准到亚像素精度。本文介绍了AGSI INR的要求和概念,图像导航模型,利用边缘和小波特征的一些潜在精度校正方法以及对所有不同误差源的研究。还描述了条带到条带相关性和通道间一致性的问题。 !19

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