Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion

The dramatic undulations of a mountainous terrain will introduce large geometric distortions in each Synthetic Aperture Radar (SAR) image with different look angles, resulting in a poor registration performance. To this end, this paper proposes a multi-hypothesis topological isomorphism matching met...

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Autores principales:	Runzhi Jiao, Qingsong Wang, Tao Lai, Haifeng Huang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	synthetic aperture radar (SAR) SAR image registration ridge detection large geometric distortion graph isomorphism Science Q
Acceso en línea:	https://doaj.org/article/f5926bbb33784ef594a077a484ba9ee3
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spelling	oai:doaj.org-article:f5926bbb33784ef594a077a484ba9ee32021-11-25T18:54:58ZMulti-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion10.3390/rs132246372072-4292https://doaj.org/article/f5926bbb33784ef594a077a484ba9ee32021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4637https://doaj.org/toc/2072-4292The dramatic undulations of a mountainous terrain will introduce large geometric distortions in each Synthetic Aperture Radar (SAR) image with different look angles, resulting in a poor registration performance. To this end, this paper proposes a multi-hypothesis topological isomorphism matching method for SAR images with large geometric distortions. The method includes the Ridge-Line Keypoint Detection (RLKD) and Multi-Hypothesis Topological Isomorphism Matching (MHTIM). Firstly, based on the analysis of the ridge structure, a ridge keypoint detection module and a keypoint similarity description method are designed, which aim to quickly produce a small number of stable matching keypoint pairs under large look angle differences and large terrain undulations. The keypoint pairs are further fed into the MHTIM module. Subsequently, the MHTIM method is proposed, which uses the stability and isomorphism of the topological structure of the keypoint set under different perspectives to generate a variety of matching hypotheses, and iteratively achieves the keypoint matching. This method uses both local and global geometric relationships between two keypoints, hence it achieving better performance compared with traditional methods. We tested our approach on both simulated and real mountain SAR images with different look angles and different elevation ranges. The experimental results demonstrate the effectiveness and stable matching performance of our approach.Runzhi JiaoQingsong WangTao LaiHaifeng HuangMDPI AGarticlesynthetic aperture radar (SAR)SAR image registrationridge detectionlarge geometric distortiongraph isomorphismScienceQENRemote Sensing, Vol 13, Iss 4637, p 4637 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	synthetic aperture radar (SAR) SAR image registration ridge detection large geometric distortion graph isomorphism Science Q
spellingShingle	synthetic aperture radar (SAR) SAR image registration ridge detection large geometric distortion graph isomorphism Science Q Runzhi Jiao Qingsong Wang Tao Lai Haifeng Huang Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion
description	The dramatic undulations of a mountainous terrain will introduce large geometric distortions in each Synthetic Aperture Radar (SAR) image with different look angles, resulting in a poor registration performance. To this end, this paper proposes a multi-hypothesis topological isomorphism matching method for SAR images with large geometric distortions. The method includes the Ridge-Line Keypoint Detection (RLKD) and Multi-Hypothesis Topological Isomorphism Matching (MHTIM). Firstly, based on the analysis of the ridge structure, a ridge keypoint detection module and a keypoint similarity description method are designed, which aim to quickly produce a small number of stable matching keypoint pairs under large look angle differences and large terrain undulations. The keypoint pairs are further fed into the MHTIM module. Subsequently, the MHTIM method is proposed, which uses the stability and isomorphism of the topological structure of the keypoint set under different perspectives to generate a variety of matching hypotheses, and iteratively achieves the keypoint matching. This method uses both local and global geometric relationships between two keypoints, hence it achieving better performance compared with traditional methods. We tested our approach on both simulated and real mountain SAR images with different look angles and different elevation ranges. The experimental results demonstrate the effectiveness and stable matching performance of our approach.
format	article
author	Runzhi Jiao Qingsong Wang Tao Lai Haifeng Huang
author_facet	Runzhi Jiao Qingsong Wang Tao Lai Haifeng Huang
author_sort	Runzhi Jiao
title	Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion
title_short	Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion
title_full	Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion
title_fullStr	Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion
title_full_unstemmed	Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion
title_sort	multi-hypothesis topological isomorphism matching method for synthetic aperture radar images with large geometric distortion
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f5926bbb33784ef594a077a484ba9ee3
work_keys_str_mv	AT runzhijiao multihypothesistopologicalisomorphismmatchingmethodforsyntheticapertureradarimageswithlargegeometricdistortion AT qingsongwang multihypothesistopologicalisomorphismmatchingmethodforsyntheticapertureradarimageswithlargegeometricdistortion AT taolai multihypothesistopologicalisomorphismmatchingmethodforsyntheticapertureradarimageswithlargegeometricdistortion AT haifenghuang multihypothesistopologicalisomorphismmatchingmethodforsyntheticapertureradarimageswithlargegeometricdistortion
_version_	1718410563909844992

Multi-Hypothesis Topological Isomorphism Matching Method for Synthetic Aperture Radar Images with Large Geometric Distortion

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