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Dimensionality reduction of hyperspectral data using spectral fractal feature / K. Mukherjee in Geocarto international, vol 27 n° 6 (October 2012)  

Public [article]  inGeocarto international > vol 27 n° 6 (October 2012) . - pp 515 - 531 Titre : Dimensionality reduction of hyperspectral data using spectral fractal feature Type de document : Article/Communication Auteurs : K. Mukherjee, Auteur ; J. Ghosh, Auteur ; R. Mittal, Auteur Année de publication : 2012 Article en page(s) : pp 515 - 531 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] courbe [Termes IGN] dimension fractale [Termes IGN] image hyperspectrale [Termes IGN] réduction [Termes IGN] réponse spectrale Résumé : (Auteur) A new approach for dimensionality reduction of hyperspectral data has been proposed in this article. The method is based on extraction of fractal-based features from the hyperspectral data. The features have been generated using spectral fractal dimension of the spectral response curves (SRCs) after smoothing, interpolating and segmenting the curves. The new features so generated have then been used to classify hyperspectral data. Comparing the post classification accuracies with some other conventional dimensionality reduction methods, it has been found that the proposed method, with less computational complexity than the conventional methods, is able to provide classification accuracy statistically equivalent to those from conventional methods. Numéro de notice : A2012-512 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.642411 Date de publication en ligne : 11/01/2012 En ligne : https://doi.org/10.1080/10106049.2011.642411 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31958 [article]

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