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Texture feature fusion with neighborhood oscillating tabu search for high resolution image classification / L. Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 3 (March 2008)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 3 (March 2008) . - pp 323 - 331 Titre : Texture feature fusion with neighborhood oscillating tabu search for high resolution image classification Type de document : Article/Communication Auteurs : L. Zhang, Auteur ; Y. Zhao, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 323 - 331 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse texturale [Termes IGN] champ aléatoire de Markov [Termes IGN] filtrage du bruit [Termes IGN] filtre de Gabor [Termes IGN] image à résolution métrique [Termes IGN] image Brodatz [Termes IGN] image Ikonos [Termes IGN] image Quickbird [Termes IGN] oscillation Résumé : (Auteur) Multi-channel Gabor filters (MGFs) and Markov random fields (MRFs) are two common methods for texture analysis. This paper investigates their integration through a novel algorithm using the neighborhood-oscillating tabu search (NOTS) for high-resolution image classification. The NOTS algorithm fuses the texture features extracted by MGF and MRF. This algorithm has been compared with classical methods such as sequential forward selection, sequential forward floating selection, and oscillating search. Experimental results show that the fused MGF/MRF features have much higher discrimination than pure features, and NOTS outperforms other algorithms with either pure or fused features. The stability and effectiveness of the proposed algorithm have been verified using Brodatz, Ikonos, and QuickBird images. Copyright ASPRS Numéro de notice : A2008-074 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.3.323 En ligne : https://doi.org/10.14358/PERS.74.3.323 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29069 [article]