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Sea state from ocean video with singular spectrum analysis and extended Kalman filter

dc.contributor.authorLoizou, A
dc.contributor.authorChristmas, J
dc.date.accessioned2021-12-20T14:19:02Z
dc.date.issued2021-12-19
dc.date.updated2021-12-20T13:57:58Z
dc.description.abstractA method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component of the movement of water in the video, which we propose is associated with the dominant frequency of the ocean. To accomplish this, the singular spectrum analysis algorithm and the extended Kalman filter are used. Then, the shape of an empirical spectrum is used in order to translate the dominant frequency output into a significant wave height estimation.en_GB
dc.identifier.citationPublished online 19 December 2021en_GB
dc.identifier.doihttps://doi.org/10.1007/s11760-021-02103-0
dc.identifier.urihttp://hdl.handle.net/10871/128169
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.rights© The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_GB
dc.subjectOcean videoen_GB
dc.subjectSea stateen_GB
dc.subjectSSA algorithmen_GB
dc.titleSea state from ocean video with singular spectrum analysis and extended Kalman filteren_GB
dc.typeArticleen_GB
dc.date.available2021-12-20T14:19:02Z
dc.identifier.issn1863-1703
dc.descriptionThis is the final version. Available on open access from Springer via the DOI in this recorden_GB
dc.identifier.eissn1863-1711
dc.identifier.journalSignal, Image and Video Processingen_GB
dc.relation.ispartofSignal, Image and Video Processing
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2021-11-26
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2021-12-19
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-12-20T13:58:17Z
refterms.versionFCDVoR
refterms.dateFOA2021-12-20T14:19:16Z
refterms.panelBen_GB
refterms.dateFirstOnline2021-12-19


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© The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's licence is described as © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.