Unpaired spatio-temporal fusion of image patches (USTFIP) from cloud covered images

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dc.contributor.authorGoyena Baroja, Harkaitz
dc.contributor.authorPérez Goya, Unai
dc.contributor.authorMontesino San Martín, Manuel
dc.contributor.authorMilitino, Ana F.
dc.contributor.authorWang, Qunming
dc.contributor.authorAtkinson, Peter M.
dc.contributor.authorUgarte Martínez, María Dolores
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.contributor.departmentInstitute for Advanced Materials and Mathematics - INAMAT2en
dc.date.accessioned2024-01-31T08:46:38Z
dc.date.available2024-01-31T08:46:38Z
dc.date.issued2023
dc.date.updated2024-01-31T08:28:31Z
dc.description.abstractSpatio-temporal image fusion aims to increase the frequency and resolution of multispectral satellite sensor images in a cost-effective manner. However, practical constraints on input data requirements and computational cost prevent a wider adoption of these methods in real case-studies. We propose an ensemble of strategies to eliminate the need for cloud-free matching pairs of satellite sensor images. The new methodology called Unpaired Spatio-Temporal Fusion of Image Patches (USTFIP) is tested in situations where classical requirements are progressively difficult to meet. Overall, the study shows that USTFIP reduces the root mean square error by 2-to-13% relative to the state-of-the-art Fit-FC fusion method, due to an efficient use of the available information. Implementation of USTFIP through parallel computing saves up to 40% of the computational time required for Fit-FC.en
dc.description.sponsorshipThis research was supported by the Spanish Research Agency and Next Generation EU (PDC2021-120796-I00 project) and by the Spanish Research Agency (PID 2020-113125RB-I00/MCIN/AEI/10.13039/ 501100011033 project). This work was supported by the National Natural Science Foundation of China under Grant 42222108.en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationGoyena, H., Pérez-Goya, U., Montesino-SanMartin, M., Militino, A. F., Wang, Q., Atkinson, P. M., & Ugarte, M. D. (2023). Unpaired spatio-temporal fusion of image patches (Ustfip) from cloud covered images. Remote Sensing of Environment, 295, 113709. https://doi.org/10.1016/j.rse.2023.113709en
dc.identifier.doi10.1016/j.rse.2023.113709
dc.identifier.issn0034-4257
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/47264
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofRemote Sensing of Environment 295 (2023) 113709en
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113125RB-I00/ES/
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PDC2021-120796-I00/ES/
dc.relation.publisherversionhttps://doi.org/10.1016/j.rse.2023.113709
dc.rights© 2023 The Author(s). This is an open access article under the CC BY-NC-ND license.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCloudsen
dc.subjectFit-FCen
dc.subjectParallel computingen
dc.subjectSatellite imageryen
dc.subjectSpatio-temporal image fusionen
dc.titleUnpaired spatio-temporal fusion of image patches (USTFIP) from cloud covered imagesen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery003960f8-aa6d-47ec-bec1-6bc59c3c8edb

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