Centre de documentation
scientifique

On comparing multifractal and classical features in minimum distance classification of AVHRR imagery / T. Parrinello in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 27 n°18 - 19 - 20 (October 2006) . - pp 3943 - 3959 Titre : On comparing multifractal and classical features in minimum distance classification of AVHRR imagery Type de document : Article/Communication Auteurs : T. Parrinello, Auteur ; R.A. Vaughan, Auteur Année de publication : 2006 Article en page(s) : pp 3943 - 3959 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] classification barycentrique [Termes IGN] classification dirigée [Termes IGN] Ecosse [Termes IGN] géométrie fractale [Termes IGN] image NOAA-AVHRR [Termes IGN] texture d'image Résumé : (Auteur) The ability to distinguish between different types of surfaces is the strength of texture descriptors in the analysis of satellite imagery. Although the most common analytical means are based on co-occurrence analysis, considerable progress has been made in understanding the role of fractal and multifractal analysis in remote sensing. After indicating the limitations of using fractal dimensions as the only texture descriptor and introducing the concept of multifractal geometry, we consider the effectiveness of using multifractal and second-order fractal features in image classification. In particular, we present the results of comparing two supervised classifications of an Advanced Very High Resolution Radiometer (AVHRR) image of Scotland using classical texture features and multifractal second-order fractal ones. In terms of percentage correct and Khat statistics, this study provides evidence, with a confidence limit of 95%, that classifications using multifractal and second-order fractal features are more accurate than those using classical features. The classification algorithm used for this study is a typical minimum distance classifier. Copyright Taylor & Francis Numéro de notice : A2006-458 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600685241 En ligne : https://doi.org/10.1080/01431160600685241 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28182 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-06101	RAB	Revue	Centre de documentation	En réserve L003	Disponible