Feature-based geometric registration of high spatial resolution satellite imagery

Yindi Zhao, Shanlei Liu, Peijun Du, Min Li
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引用次数: 8

Abstract

Image registration is a crucial step in some specific applications of remote sensing. High resolution remote sensing images have made it more convenient for people to observe the Earth; however, they also create challenges for traditional research methods. In terms of image registration, there are a number of problems with using conventional image registration techniques for high resolution images. This paper develops an improved feature-based geometric registration approach for high spatial resolution images, in which control points are efficiently selected automatically. First a modified watershed transformation algorithm is used for image segmentation. Then regions are represented by centers of gravity, and road intersection can be considered the main target to perform the control point extraction. Secondly the extracted points in the reference and warped images can be matched using spatial relations. Finally, pixels in the warped image are directly corrected using the chosen geometric model followed by the corresponding interpolation methods. The proposed feature-based geometric correction method is implemented using a time series of QuickBird images acquired over the 2004/2005 summer season at Xuzhou City, Jiangsu Province of China. The experimental results show that the presented rectification approach is convenient to determine ground control points, and is efficient for high spatial resolution image geometric registration.
基于特征的高空间分辨率卫星图像几何配准
图像配准是遥感某些特定应用的关键步骤。高分辨率的遥感影像为人们观测地球提供了便利;然而,它们也给传统的研究方法带来了挑战。在图像配准方面,使用传统的图像配准技术对高分辨率图像进行配准存在许多问题。本文提出了一种改进的基于特征的高空间分辨率图像几何配准方法,该方法可以自动高效地选择控制点。首先采用改进的分水岭变换算法进行图像分割。然后用重心表示区域,以道路交叉口为主要目标进行控制点提取。其次,利用空间关系对参考图像和变形图像中的提取点进行匹配。最后,使用选择的几何模型和相应的插值方法直接对扭曲图像中的像素进行校正。利用2004/2005年中国江苏省徐州市夏季QuickBird图像的时间序列,实现了基于特征的几何校正方法。实验结果表明,该校正方法可以方便地确定地面控制点,并能有效地实现高空间分辨率图像的几何配准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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