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Geometric Correction of High Resolution Satellite Imagery and its Residual Analysis

机译:高分辨率卫星图像的几何校正及其残余分析

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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 we 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 we 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.
机译:高分辨率卫星图像易于几何扭曲。为了纠正这些,几何校正的过程变得至关重要。只有知识卫星高度,姿态,位置和数字高度模型(DEM)信息的知识将不足以适用于几何校正要求。因此,我们设计了一种用于去除卫星图像中几何失真的算法。从而应用于称为像素投影方法的地理参考方法以及精确的地面控制点(GCP)的选择。在像素投影方法中,远程感测图像的顶点是基于辅助数据的地理位置。对于GCP最小二乘法的精确度,用于迎合仪器偏压。 GCP选自Google地球软件。然而,通过该方法,实现了精确的地理参考卫星图像,并且成功转换为级别-3几何校正图像。本文对我们的新方法进行了残余分析。在第一步骤中,执行到图像匹配的图像,并计算它们的MSE(均方误差)。在第二步骤8中,识别出原始图像和地理参考图像中的点,并计算它们的MSE。观察到,已经完成了新的地理参考方法,已经完成了更精确的地理参考,并且发现图像被准确地校正。

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