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Adaptive registration of remote sensing images using supervised learning / L. Eikvil in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 11 (November 2009)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 11 (November 2009) . - pp 1297 - 1306 Titre : Adaptive registration of remote sensing images using supervised learning Type de document : Article/Communication Auteurs : L. Eikvil, Auteur ; M. Holden, Auteur ; R.B. Huseby, Auteur Année de publication : 2009 Article en page(s) : pp 1297 - 1306 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] appariement d'images [Termes IGN] apprentissage dirigé [Termes IGN] image satellite [Termes IGN] série temporelle [Termes IGN] superposition d'images Résumé : (Auteur) This paper describes a system for co-registration of time series satellite images which uses a learning-based strategy. During a training phase, the system learns to recognize regions in an image suited for registration. It also learns the relationship between image characteristics and registration performance for a set of different registration algorithms. This enables intelligent selection of an appropriate registration algorithm for each region in the image, while regions unsuited for registration can be discarded. The approach is intended for co-registration of sequences of images acquired from identical or similar earth observation sensors. It has been tested for such sequences from different types of sensors, both optical and radar, with varying resolution. For images with moderate differences in content, the registration accuracy is, in general, good with an RMS error of one pixel or less. Copyright ASPRS Numéro de notice : A2009-442 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.11.1297 En ligne : https://doi.org/10.14358/PERS.75.11.1297 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30073 [article]