高分辨率卫星图像几何校正及其残差分析

F. Arif, M. Akbar, A. Wu
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引用次数: 3

摘要

高分辨率卫星图像容易产生几何畸变。为了纠正这些,几何校正过程变得至关重要。仅知道卫星的高度、姿态、位置和数字高程模型(DEM)的信息是不足以满足几何校正要求的。为此,作者设计了一种去除卫星图像几何畸变的算法。其中采用了一种新的地理参考方法——像素投影法,并选择了精确的地面控制点(gcp)。在像素投影法中,遥感影像的顶点是基于辅助数据进行地理定位的。为了提高GCP的精度,采用最小二乘法来考虑仪器偏差。gcp是从谷歌Earth软件中选择的。通过这种方法,实现了卫星图像的精确地理参考,并成功地将一级图像转换为三级几何校正图像。本文作者对我们提出的新方法进行了残差分析。首先对图像进行匹配,计算图像的均方误差(MSE)。第二步,对原始图像和地理参考图像中的8个点进行识别,并计算其MSE。结果表明,采用新的参考方法可以实现更精确的参考,并对图像进行了精确的几何校正
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geometric Correction of High Resolution Satellite Imagery and its Residual Analysis
High resolution satellite images are prone to geometric distortions. To correct these, the process of geometric correction becomes vital. Only knowledge of satellite altitude, attitude, position and the information of the digital elevation model (DEM) will not be adequate for the geometric correction requirements. Therefore the authors designed an algorithm for removal of geometric distortions in satellite imagery. In that a new method of geo-referencing called pixel projection method was applied along with selection of precise ground control points (GCPs). In pixel projection method vertices of remotely sensed image is geo-located based on ancillary data. For precision of GCP least square method was used to cater for instrument bias. GCPs were selected from Google Earth's software. Though with that approach precise geo-referencing of satellite imagery was achieved and a level-1 image was successfully converted to level-3 geometrically corrected image. In this paper the authors carried out residual analysis of our new proposed method. In first step an image to image matching was performed and their MSE (mean square error) was calculated. In second step 8 points in the original image and geo-referenced images were identified and their MSE was calculated. It is observed that with new approach of geo-referencing more precise geo-referencing has been done and image is found to be accurately geometrically corrected
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