Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31506
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dc.contributor.authorSilva, Ewertonen_UK
dc.contributor.authorTorres, Ricardo da Sen_UK
dc.contributor.authorAlberton, Brunaen_UK
dc.contributor.authorMorellato, Leonor Patricia Cen_UK
dc.contributor.authorSilva, Thiago S Fen_UK
dc.date.accessioned2020-08-01T00:04:45Z-
dc.date.available2020-08-01T00:04:45Z-
dc.date.issued2020-05en_UK
dc.identifier.other14en_UK
dc.identifier.urihttp://hdl.handle.net/1893/31506-
dc.description.abstractOne of the challenges in remote phenology studies lies in how to efficiently manage large volumes of data obtained as long-term sequences of high-resolution images. A promising approach is known as image foveation, which is able to reduce the computational resources used (i.e., memory storage) in several applications. In this paper, we propose an image foveation approach towards plant phenology tracking where relevant changes within an image time series guide the creation of foveal models used to resample unseen images. By doing so, images are taken to a space-variant domain where regions vary in resolution according to their contextual relevance for the application. We performed our validation on a dataset of vegetation image sequences previously used in plant phenology studies.en_UK
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.relationSilva E, Torres RdS, Alberton B, Morellato LPC & Silva TSF (2020) A Change-Driven Image Foveation Approach for Tracking Plant Phenology. Remote Sensing, 12 (9), Art. No.: 14. https://doi.org/10.3390/rs12091409en_UK
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citeden_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectfoveal modelen_UK
dc.subjectimage foveationen_UK
dc.subjecthilbert curveen_UK
dc.subjectplant phenology trackingen_UK
dc.subjectspace-variant imageen_UK
dc.titleA Change-Driven Image Foveation Approach for Tracking Plant Phenologyen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.3390/rs12091409en_UK
dc.citation.jtitleRemote Sensingen_UK
dc.citation.issn2072-4292en_UK
dc.citation.volume12en_UK
dc.citation.issue9en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderBrazilian National Research Councilen_UK
dc.citation.date29/04/2020en_UK
dc.contributor.affiliationUniversity of Campinasen_UK
dc.contributor.affiliationNorwegian University of Science And Technology (NTNU)en_UK
dc.contributor.affiliationSao Paulo State University (Universidade Estadual Paulista)en_UK
dc.contributor.affiliationSao Paulo State University (Universidade Estadual Paulista)en_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.identifier.isiWOS:000543394000056en_UK
dc.identifier.scopusid2-s2.0-85085244878en_UK
dc.identifier.wtid1648751en_UK
dc.contributor.orcid0000-0001-8174-0489en_UK
dc.date.accepted2020-04-26en_UK
dc.date.filedepositdate2020-07-30en_UK
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