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An adaptive semisupervised approach to the detection of user-defined recurrent changes in image time series / Daniel Zanotta in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 7 (July 2015) . - pp 3707 - 3719 Titre : An adaptive semisupervised approach to the detection of user-defined recurrent changes in image time series Type de document : Article/Communication Auteurs : Daniel Zanotta, Auteur ; Lorenzo Bruzzone, Auteur ; Francesca Bovolo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 3707 - 3719 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] forêt [Termes IGN] image Landsat-TM [Termes IGN] incendie de forêt [Termes IGN] série temporelle Résumé : (Auteur) In this paper, we present a novel domain adaptation technique aimed at providing reliable change detection maps for a series of image pairs acquired on the same area at different times. The proposed technique exploits the polar change vector analysis method and assumes that the reference data for characterizing a specific change of interest are available only for a pair of images (source domain). Then, it exploits the knowledge learned from the source domain and adapts it to other pairs of images belonging to the time series (target domains) to be analyzed. The proposed technique is able to handle possible radiometric differences among images adapting in an unsupervised way the decision rule estimated on the source domain to the target domains through variables estimated directly on the target images. The proposed approach has been applied to two data sets made up of time series of Landsat Thematic Mapper images. In one case, the change of interest is related to evolution of deforestation, while in the other case, it is related to burned area detection. Experimental results show the effectiveness of the proposed technique. Numéro de notice : A2015-321 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2381645 En ligne : https://doi.org/10.1109/TGRS.2014.2381645 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76574 [article]

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