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.

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