Centre de documentation
scientifique

Linear features extraction in rain forest context from interferometric SAR images by fusion of coherence and amplitude information / V.P. Onana in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 41 n° 11 (November 2003) . - pp 2540 - 2556 Titre : Linear features extraction in rain forest context from interferometric SAR images by fusion of coherence and amplitude information Type de document : Article/Communication Auteurs : V.P. Onana, Auteur ; Emmanuel Trouvé, Auteur ; G. Mauris, Auteur ; Jean-Paul Rudant , Auteur ; E. Tonye, Auteur Année de publication : 2003 Article en page(s) : pp 2540 - 2556 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] Cameroun [Termes IGN] classification barycentrique [Termes IGN] classification floue [Termes IGN] détection de contours [Termes IGN] extraction de traits caractéristiques [Termes IGN] forêt tropicale [Termes IGN] fusion d'images [Termes IGN] image ERS-SAR [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] littoral [Termes IGN] mangrove [Termes IGN] objet géographique linéaire Résumé : (Auteur) This paper presents an almost unsupervised fusion algorithm on linear features (LF) extraction in synthetic aperture radar (SAR) interferometric data, in particular for mangroves/shorelines and thin internal channels. The spatial information on LFs is first extracted in the coherence image, where they are wider and more visible : water regions (in particular thin internal channels) are dark areas (low coherence) due to the temporal decorrelation of backscattering signals in these and surrounding regions, whereas conventional vegetation regions are brighter areas (high coherence). These approximate locations of LFs are further refined by using the edge map coming from a semantic fuzzy fusion of the coefficient of variation (CV) and the ratio of local means (RLM) measured in the amplitude image. The final detection of LFs is then performed by merging the two fuzzy inputs : the spatial information and the edge location map. The membership degree statistics of CV and RLM semantic fusion measures are introduced in order to illustrate the location detection ability. The originality of this method in comparison with conventional approaches is in the fusion scheme that follows the interpreter behavior by using first the coherence image for a fuzzy detection where thin LFs are more visible, but have low location accuracy, and then the amplitude image where they are poorly visible, but with higher location accuracy, to obtain improved results. A quantitative performance evaluation is also presented. The method has been applied on real interferometric SAR images from European Remote Sensing satellites over the western part of Cameroon. Numéro de notice : A2003-321 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.818383 En ligne : https://doi.org/10.1109/TGRS.2003.818383 Format de la ressource électronique : URl article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22617 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-03111	RAB	Revue	Centre de documentation	En réserve L003	Disponible