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Fuzzy image segmentation for urban land-cover classification / I. Lizarazo in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 2 (February 2010)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 2 (February 2010) . - pp 151 - 162 Titre : Fuzzy image segmentation for urban land-cover classification Type de document : Article/Communication Auteurs : I. Lizarazo, Auteur ; J. Barros, Auteur Année de publication : 2010 Article en page(s) : pp 151 - 162 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse d'image orientée objet [Termes IGN] classification dirigée [Termes IGN] classification orientée objet [Termes IGN] exploration de données géographiques [Termes IGN] image à haute résolution [Termes IGN] occupation du sol [Termes IGN] segmentation d'image [Termes IGN] zone urbaine Résumé : (Auteur) A main problem of hard image segmentation is that, in complex landscapes, such as urban areas, it is very hard to produce meaningful crisp image-objects. This paper proposes a fuzzy approach for image segmentation aimed to produce fuzzy image-regions expressing degrees of membership of pixels to different target classes. This approach, called Fuzzy Image-Regions Method (FIRME), is a natural way to deal with the inherent ambiguity of remotely sensed images. The FIRME approach comprises three main stages: (a) image segmenta-tion which creates fuzzy image-regions, (b) feature analysis which measures properties of fuzzy image regions, and (c) classification which produces the intended land-cover classes. The FIRME method was evaluated in a land-cover classification experiment using high spectral resolution imagery in an urban zone in Bogota, Colombia. Results suggest that in complex environments, fuzzy image segmen-tation may be a suitable alternative for GEOBIA as it produces higher thematic accuracy than the hard image segmentation and other traditional classifiers. Copyright ASPRS Numéro de notice : A2010-049 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.76.2.151 En ligne : https://doi.org/10.14358/PERS.76.2.151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30245 [article]