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Proceedings Paper

Multi-source remote-sensing image matching based on epipolar line and least squares
Author(s): Peng Chen; Zhihua Mao; Jianyu Chen; Xiaoping Zhang; Zifeng Li
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Paper Abstract

In remote sensing image applications, the image matching is a very key technology, its quality directly related to the quality of the subsequent results. This paper studied an improved SIFT features matching method for muili-source remote-sensing image registration based on GPU computing, epipolar line and least squares, its main purpose is to take both accuracy and efficiency into consideration. This method is firstly based on tonal balanced methods matching, and then exracts SIFT features based on the GPU computing technology, and then matchs feature points based on epipolar line and least squares matching method with RANSAC method, finally analies error sources of SIFT mismatch, researchs an improved SIFT mismatch reduce strategy.The experimental results prove that the method can effectively improve the efficiency and precision of SIFT feature matching.

Paper Details

Date Published: 17 October 2013
PDF: 7 pages
Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 88921N (17 October 2013); doi: 10.1117/12.2030097
Show Author Affiliations
Peng Chen, Wuhan Univ. (China)
Zhihua Mao, The Second Institute of Oceanography, SOA (China)
Jianyu Chen, The Second Institute of Oceanography, SOA (China)
Xiaoping Zhang, Wuhan Univ. (China)
Zifeng Li, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 8892:
Image and Signal Processing for Remote Sensing XIX
Lorenzo Bruzzone, Editor(s)

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