A Multi-source Remote Sensing Image Matching Method Using Directional Phase Feature

LI Xin; YANG Yuhui; YANG Bo; YIN FENG

doi:10.13203/j.whugis20180445

Volume 45 Issue 4

Apr. 2020

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Geomatics and Information Science of Wuhan University > 2020 > 45(4): 488-494. > DOI: 10.13203/j.whugis20180445

LI Xin, YANG Yuhui, YANG Bo, YIN FENG. A Multi-source Remote Sensing Image Matching Method Using Directional Phase Feature[J]. Geomatics and Information Science of Wuhan University, 2020, 45(4): 488-494. DOI: 10.13203/j.whugis20180445

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A Multi-source Remote Sensing Image Matching Method Using Directional Phase Feature

LI Xin^1,,
YANG Yuhui^1, ,,
YANG Bo²,
YIN FENG³

1.
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
3.
Hubei Institute of Land and Resources, Wuhan 430071, China

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Author Bio:
LI Xin, PhD, professor. He is concentrated on the research and teaching in photogrammetry and remote sensing. xli2126@whu.edu.cn
Corresponding author:
YANG Yuhui, postgraduate. yuhuiyang@whu.edu.cn
Received Date: April 12, 2019
Published Date: April 04, 2020

Graphical Abstract

Abstract

Abstract

A multi-source remote sensing image matching method using directional phase feature is proposed to solve the problem of matching multi-source remote sensing images with nonlinear radiometric differences. Firstly, feature points of reference image are extracted uniformly. And then phase congruency energy images in multiple directions are calculated using Log-Gabor filters. Dense character descriptions of feature points of the reference image are built. Finally, correspondences are obtained by sliding matching window and Taylor series expansion is used to fit to the sub pixel accuracy. Experiments on three groups of real heterogeneous remote sensing images show that the proposed method can achieve stable and reliable matching results on optical, infrared, multi-spectral and SAR (synthetic aperture radar)images.
- directional phase congruency,
- multi-source remote sensing image,
- feature points,
- image matching

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