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Performance evaluation of object-based and pixel-based building detection algorithms from very high spatial resolution imagery / Iman Khosravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 6 (June 2014) . - pp 519 - 528 Titre : Performance evaluation of object-based and pixel-based building detection algorithms from very high spatial resolution imagery Type de document : Article/Communication Auteurs : Iman Khosravi, Auteur ; Mehdi Momeni, Auteur ; Maryam Rahnemoonfar, Auteur Année de publication : 2014 Article en page(s) : pp 519 - 528 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] classification orientée objet [Termes IGN] classification pixellaire [Termes IGN] détection du bâti [Termes IGN] erreur de classification [Termes IGN] image à très haute résolution [Termes IGN] segmentation d'image Résumé : (Auteur) Building detection from remote sensed images is the main technique to monitor economic or environmental develop-ment of an area. Advanced Land Observing Satellite (alos) and SPOT data are reliable sources due to the limitation of weather, position, time, and other practical reasons. How-ever, to the best of our knowledge, algorithms proposed in the identification of buildings mostly aim only at images with very high spatial resolution or high spectral resolution. There are few algorithms for detecting buildings from ALOS and SPOT data. A built-up detection index (bdi) is proposed in this paper to automatically identify buildings from images with 10 meters resolution. It synthesizes morphological theory and normalized differential vegetation index (NDVl) to enhance buildings by suppressing vegetation. Four images of ALOS and SPOT are used to verify the efficiency, stability and ac-curacy of BDI. Experiments show that BDI is suitable to detect buildings from 10 meters resolution with reliable accuracy. Numéro de notice : A2014-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.6.519-528 En ligne : https://doi.org/10.14358/PERS.80.6.519-528 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33194 [article]