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Automatic registration of coastal remotely sensed imagery by affine invariant feature matching with shoreline constraint / Liang Cheng in Marine geodesy, vol 37 n° 1 (March - May 2014)  

Public [article]  inMarine geodesy > vol 37 n° 1 (March - May 2014) . - pp 32 - 46 Titre : Automatic registration of coastal remotely sensed imagery by affine invariant feature matching with shoreline constraint Type de document : Article/Communication Auteurs : Liang Cheng, Auteur ; Lihua Tong, Auteur ; Yongxue Liu, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 32 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] couple stéréoscopique [Termes IGN] littoral [Termes IGN] Ransac (algorithme) [Termes IGN] télédétection spatiale [Termes IGN] trait de côte Résumé : (Auteur) A new approach based on Affine Invariant Feature Matching (AIFM) with a filtering technique is proposed for automatic registration of remotely sensed image in coastal areas. The novelty of this approach is an automatic filtering technique using RANdom SAmple Consensus (RANSAC) with shoreline constraint for AIFM to remove all wrong matches and simultaneously keep as many correct matches as possible. To implement it, a progressive threshold strategy (from small value to large value) is presented to determine an appropriate RANSAC threshold, in which the progressive process is guided by shoreline constraint. The proposed approach (with filtering) is compared with standard AIFM (without filtering) using two typical image pairs in coastal areas. The experimental results indicate that the proposed approach can always provide much better matching results than standard AIFM. Numéro de notice : A2015-162 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01490419.2013.868382 Date de publication en ligne : 02/08/2013 En ligne : https://doi.org/10.1080/01490419.2013.868382 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75849 [article]

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