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Type: Conference paper
Title: Automatic remote-sensing images registration by matching close-regions
Author: Xie, G.
Shen, H.
Citation: Parallel and distributed processing and applications : international symposium, ISPA 2003, Aizu-Wakamatsu, Japan, July 2-4, 2003 : proceedings / Minyi Guo, Laurence Tianruo Yang (eds.), pp. 316-328
Publisher: Springer
Publisher Place: Berlin
Issue Date: 2003
Series/Report no.: Lecture notes in computer science, 2745
ISBN: 3540405232
ISSN: 0302-9743
Conference Name: ISPA 2003 (2003 : Aizuwakamatsu-shi, Japan)
Statement of
Gui Xie, Hong Shen
Abstract: Remote-sensing images registration is a fundamental task in image processing, which is concerned with establishment of correspondence between two or more pictures taken, for example, at different times, from different sensors, or from different viewpoints. Because of the different gray level characters in such remote-sensing images, it's difficult to match them automatically. We usually constrain the images to some particular categories, or do the job manually. In this paper, we develop a new algorithm for remote-sensing images registration, which takes full advantage of the shape information of the close-regions bounded by contours after detecting and linking the edges in images. Based on the shape-specific points of the close-regions, we match the close-regions by evaluating their matching degrees. Using the matched pairs of the close-regions, the geometric parameters for images registration are computed and this registration task can be performed automatically and accurately. This new algorithm works well for those images where the contour information is well preserved, such as the optical images from LANDSAT and SPOT satellites. Experiments verified our algorithm, and showed that the performance of executing it sequentially depends a lot on the size of the input images. The time complexity will increase exponentially as the size of images increases. So we extend the sequential algorithm to a distributed scheme and perform the registration task more efficiently.
Description: The original publication is available at
RMID: 0020065795
DOI: 10.1007/3-540-37619-4_32
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Appears in Collections:Computer Science publications

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