13 March 2020 Image registration approach with scale-invariant feature transform algorithm and tangent-crossing-point feature
Zhili Song, Jiaqi Zhang
Author Affiliations +
Abstract

Due to considerable diversities of multimodality remote sensing images in spectral component, the performances of scale-invariant feature transform (or SIFT) may be problematic. In view of this, a model of image registration based on tangent-crossing-point feature is proposed. With the help of tangent-cross-point feature, verifying the correctness of the feature matching is very easy, since it adopts the location information indexed by the correct matching pair of feature-points and transformation information determined by the correct matching pair of curves simultaneously. Experimental results show that this method is more efficient and reliable than the classic SIFT algorithm in some cases.

© 2020 SPIE and IS&T 1017-9909/2020/$28.00 © 2020 SPIE and IS&T
Zhili Song and Jiaqi Zhang "Image registration approach with scale-invariant feature transform algorithm and tangent-crossing-point feature," Journal of Electronic Imaging 29(2), 023010 (13 March 2020). https://doi.org/10.1117/1.JEI.29.2.023010
Received: 22 August 2019; Accepted: 25 February 2020; Published: 13 March 2020
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image registration

Lawrencium

Remote sensing

Picosecond phenomena

Image processing

Earth observing sensors

Landsat

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