Centre de documentation
scientifique

N-FindR method versus independent component analysis for lithological identification in hyperspectral imagery / C. Gomez in International Journal of Remote Sensing IJRS, vol 28 n°23-24 (December 2007)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 28 n°23-24 (December 2007) . - pp 5315 - 5338 Titre : N-FindR method versus independent component analysis for lithological identification in hyperspectral imagery Type de document : Article/Communication Auteurs : C. Gomez, Auteur ; H. Le Borgne, Auteur ; P. Allemand, Auteur ; C. Delacourt, Auteur ; P. Ledru, Auteur Année de publication : 2007 Article en page(s) : pp 5315 - 5338 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse des mélanges spectraux [Termes IGN] analyse en composantes indépendantes [Termes IGN] classification automatique [Termes IGN] image EO1-Hyperion [Termes IGN] image hyperspectrale [Termes IGN] lithologie [Termes IGN] méthode robuste [Termes IGN] Namibie [Termes IGN] photo-interprétation assistée par ordinateur Résumé : (Auteur) The current study addresses the problem of the identification of each natural material present in each pixel of a hyperspectral image. Two end member extraction methods from hyperspectral imagery were studied: the N-FindR method and the independent component analysis (ICA). The N-FindR is an automatic technique that selects extreme points (end members) of an n-dimensional scatter plot. It assumes the existence of pure pixels in the distribution, which is infrequent in practice. ICA is a blind source separation technique studied in the signal processing community, which allows each spectrum of natural elements (end member spectra) to be extracted from the observation of some linear combinations of these. It considers a more realistic situation than N-FindR, assuming a spectra mixture for all the pixels. To increase the robustness of ICA, continuum-removed reflectance spectra were used and an iterative algorithm was introduced that takes into account a major part of the available information. The end member abundances were estimated by the fully constrained least squares spectral mixture analysis (FLCS). The end member identification and quantification were carried out on two surficial formations of a semi arid region located in the Rehoboth region, in Namibia, from hyperspectral Hyperion data. It appears that the two end member extraction methods have a similar potential. Whichever end member extraction method is used, the analysis of the rock abundance maps produces a lot of geological information: the distribution of natural elements is in line with the field observations and allows the description of the formation processes of surficial units. Copyright Taylor & Francis Numéro de notice : A2007-536 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701227679 En ligne : https://doi.org/10.1080/01431160701227679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28899 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-07131	RAB	Revue	Centre de documentation	En réserve L003	Disponible