Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-11030
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dc.contributor.authorYe, Zhen-
dc.contributor.authorKang, Jian-
dc.contributor.authorYao, Jing-
dc.contributor.authorSong, Wenping-
dc.contributor.authorLiu, Sicong-
dc.contributor.authorLuo, Xin-
dc.contributor.authorXu, Yusheng-
dc.contributor.authorTong, Xiaohua-
dc.date.accessioned2020-12-09T11:33:13Z-
dc.date.available2020-12-09T11:33:13Z-
dc.date.issued2020-08-04-
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/12156-
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-11030-
dc.description.abstractAutomatic fine registration of multisensor images plays an essential role in many remote sensing applications. However, it is always a challenging task due to significant radiometric and textural differences. In this paper, an enhanced subpixel phase correlation method is proposed, which embeds phase congruency-based structural representation, L1-norm-based rank-one matrix approximation with adaptive masking, and stable robust model fitting into the conventional calculation framework in the frequency domain. The aim is to improve the accuracy and robustness of subpixel translation estimation in practical cases. In addition, template matching using the enhanced subpixel phase correlation is integrated to realize reliable fine registration, which is able to extract a sufficient number of well-distributed and high-accuracy tie points and reduce the local misalignment for coarsely coregistered multisensor remote sensing images. Experiments undertaken with images from different satellites and sensors were carried out in two parts: tie point matching and fine registration. The results of qualitative analysis and quantitative comparison with the state-of-the-art area-based and feature-based matching methods demonstrate the effectiveness and reliability of the proposed method for multisensor matching and registration.en
dc.description.sponsorshipTU Berlin, Open-Access-Mittel – 2020en
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc620 Ingenieurwissenschaften und zugeordnete Tätigkeitende
dc.subject.otherimage registrationen
dc.subject.othersubpixel matchingen
dc.subject.otherphase correlationen
dc.subject.othermultisensor remote sensing imagesen
dc.subject.otherfine registrationen
dc.titleRobust Fine Registration of Multisensor Remote Sensing Images Based on Enhanced Subpixel Phase Correlationen
dc.typeArticleen
dc.date.updated2020-09-02T15:35:28Z-
tub.accessrights.dnbfreeen
tub.publisher.universityorinstitutionTechnische Universität Berlinen
dc.identifier.eissn1424-8220-
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.doi10.3390/s20154338en
dcterms.bibliographicCitation.journaltitleSensorsen
dcterms.bibliographicCitation.originalpublisherplaceBaselen
dcterms.bibliographicCitation.volume20en
dcterms.bibliographicCitation.originalpublishernameMDPIen
dcterms.bibliographicCitation.issue15en
dcterms.bibliographicCitation.articlenumber4338en
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