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Multiple classifier systems for supervised remote sensing image classification based on dynamic classifier selection / P.C. Smits in IEEE Transactions on geoscience and remote sensing, vol 40 n° 4 (April 2002)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 40 n° 4 (April 2002) . - pp 801 - 813 Titre : Multiple classifier systems for supervised remote sensing image classification based on dynamic classifier selection Type de document : Article/Communication Auteurs : P.C. Smits, Auteur Année de publication : 2002 Article en page(s) : pp 801 - 813 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] classification dirigée [Termes IGN] manipulation dynamique de données Résumé : (Auteur) In the literature, multiple classifier systems (MCSs) have proved to be a valuable approach to combining classifiers, and under some conditions MCSs are able to mimic ideal Bayesian labeling. This paper focuses on the family of MCSs based on dynamic classifier selection (DCS) and proposes a modification to dynamic classifier selection by local accuracy (DCS-LA). Experiments show that the proposed method outperform MCS strategies based on belief functions and the DCS-LA in terms of minimum and maximum class accuracies and kappa coefficient of agreement and is a valid alternative to majority voting. Moreover, the experiments show that MCSs based on the classification results of classifiers characterized by a low design complexity like maximum likelihood and nearest mean classifiers can yield accuracies that are quite comparable to those of highly optimized classifiers. Numéro de notice : A2002-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.1006354 En ligne : https://doi.org/10.1109/TGRS.2002.1006354 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22092 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-02041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
065-02042	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Object detection using transformed signatures in multitemporal hyperspectral imagery / R. Mayer in IEEE Transactions on geoscience and remote sensing, vol 40 n° 4 (April 2002)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 40 n° 4 (April 2002) . - pp 831 - 840 Titre : Object detection using transformed signatures in multitemporal hyperspectral imagery Type de document : Article/Communication Auteurs : R. Mayer, Auteur ; R. Priest, Auteur Année de publication : 2002 Article en page(s) : pp 831 - 840 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] extraction de traits caractéristiques [Termes IGN] image hyperspectrale [Termes IGN] image multitemporelle [Termes IGN] recouvrement d'images [Termes IGN] signature spectrale [Termes IGN] superposition d'images Résumé : (Auteur) Changes in atmosphere, ground conditions, and sensor response between multitemporal airborne imaging sessions have limited the use of fixed target hyperspectral libraries in helping to identify targets in heterogeneous (cluttered) backgrounds. This hyperspectral target signature instability has resulted in using anomaly detection algorithms to detect targets in real time applications. The anomaly detection algorithms, however, have not detected targets at sufficiently low false alarm rates. This study examines mathematical transforms of target spectral signatures. Specifically this study uses statistical information regarding background clutter taken from one long-wave infrared (LWIR) hyperspectral (8-12jum) airborne imagery flown on one day, to find the target spectral signature flown on another day (with significantly dissimilar weather conditions). The transforms use overlapping regions in the two data sets but without subpixel level registration. This work analyzes image cubes collected during the November 1998 Hyperspectral Day/Night Radiometry Assessment (HYDRA) data collect. The transformed signatures used in matched filter searches successfully find targets (even targets nearly covered) with low false alarm rates ( Numéro de notice : A2002-178 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.1006361 En ligne : https://doi.org/10.1109/TGRS.2002.1006361 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22093 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-02041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
065-02042	RAB	Revue	Centre de documentation	En réserve L003	Disponible