NDLI: Hierarchical hybrid multi-scale feature match

Content Provider	IEEE Xplore Digital Library
Author	Zeng-Shun Zhao Qing-Ji Tian Ji-Zhen Wang Xue-Zhen Cheng Mao-Yong Cao
Copyright Year	2010
Description	Author affiliation: College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266510, China (Zeng-Shun Zhao; Qing-Ji Tian; Ji-Zhen Wang; Xue-Zhen Cheng; Mao-Yong Cao)
Abstract	Finding reliable corresponding points between two images of a scene is a fundamental problem in computer vision. In this paper, a hybrid scheme is proposed, which combines invariant spatial feature and frequency domain based methods in a hierarchical multi-scale way. The Fourier-Mellin Transform is applied to obtain the transformation parameters at the coarse level between the two images; then, the parameters can serve as the initial guess, to guide the following feature matching step at the original scale, where the correspondences are restricted in a search window determined by the warp between the reference image and the current image; Finally, the transformation parameters are refined by a RANSAC procedure. This in return provides a more accurate result for feature correspondence. Experiments show that our approach provides satisfactory feature matching performance. This method also makes precise geometric rectification to remote sensing imagery.
Starting Page	1653
Ending Page	1656
File Size	365173
Page Count	4
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5647734
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	RANSAC Computer vision Image registration multi-scale Estimation Transforms Feature extraction Fourier-Mellin Transform Robustness Feature correspondence Frequency domain analysis
Content Type	Text
Resource Type	Article

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