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Clustering of detected changes in high-resolution satellite imagery using a stabilized competitive agglomeration algorithm / O. Sjahputera in IEEE Transactions on geoscience and remote sensing, vol 49 n° 12 Tome 1 (December 2011)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 49 n° 12 Tome 1 (December 2011) . - pp 4687 - 4703 Titre : Clustering of detected changes in high-resolution satellite imagery using a stabilized competitive agglomeration algorithm Type de document : Article/Communication Auteurs : O. Sjahputera, Auteur ; G. Scott, Auteur ; B. Claywell, Auteur ; et al., Auteur Année de publication : 2011 Article en page(s) : pp 4687 - 4703 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse de groupement [Termes IGN] chevauchement [Termes IGN] classification floue [Termes IGN] dalle [Termes IGN] détection de changement [Termes IGN] image à haute résolution [Termes IGN] mosaïque d'images Résumé : (Auteur) The Geospatial Change Detection and exploitation (GeoCDX) is a fully automated system for detection and exploitation of change between multitemporal high-resolution satellite and airborne images. Overlapping multitemporal images are first organized into 256 m x 256 m tiles in a global grid reference system. The system quantifies the overall amount of change in a given tile with a tile change score as an aggregation of pixel-level changes. The tiles are initially ranked by these change scores for retrieval, review, and exploitation in a Web-based application. However, the ranking does not account for the wide variety of change types that are typically observed in the top-ranked change tiles. To automatically organize the wide variety of change patterns observed in multitemporal high-resolution imagery, we perform tile clustering using the competitive agglomeration (CA) algorithm stabilized using the fuzzy c-means (FCM) algorithm. Each resulting cluster contains tiles with a visually similar type of change. By visual inspection of these tile clusters, GeoCDX users can quickly find certain types of change without having to sift through a large number of tiles initially organized solely by their tile change score, thereby reducing the time it takes for users to discover and exploit the change pattern(s) of greatest interest to a given application (e.g., urban growth, disaster assessment, facility monitoring, etc.). The tile clusters also provide a high-level overview of the various types of change that occur between the two observations. This overview is compared with a similar yet more limited view offered by a relevance feedback tool that requires a user to select sample tiles for use as samples in the reranking process. Numéro de notice : A2011-477 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2152847 Date de publication en ligne : 22/12/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2152847 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31371 [article]

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