Descripteur
Documents disponibles dans cette catégorie (853)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Best-bases feature extraction algorithms for classification of hyperspectral data / Satish Kumar in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
[article]
Titre : Best-bases feature extraction algorithms for classification of hyperspectral data Type de document : Article/Communication Auteurs : Satish Kumar, Auteur ; J. Ghosh, Auteur ; Melba M. Crawford, Auteur Année de publication : 2001 Article en page(s) : pp 1368 - 1379 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] précision de la classificationRésumé : (Auteur) Due to advances in sensor technology, it is now possible to acquire hyperspectral data simultaneously in hundreds of bands. Algorithms that both reduce the dimensionality of the data sets and handle highly correlated bands are required to exploit the information in these data sets effectively. the authors propose a set of best-bases feature extraction algorithms that are simple, fast, and highly effective for classification of hyperspectral data. These techniques intelligently combine subsets of adjacent bands into a smaller number of features. Both top-down and bottom-up algorithms are proposed. The top-down algorithm recursively partitions the bands into two (not necessarily equal) sets of bands and then replaces each final set of bands by its mean value. The bottom-up algorithm builds an agglomerative tree by merging highly correlated adjacent bands and projecting them onto their Fisher direction, yielding high discrimination among classes. Both these algorithms are used in a pairwise classifier framework where the original C-class problem is divided into a set of (2C) two-class problems. The new algorithms (1) find variable length bases localized in wavelength, (2) favor grouping highly correlated adjacent bands that, when merged either by taking their mean or Fisher linear projection, yield maximum discrimination, and (3) seek orthogonal bases for each of the (2C) two-class problems into which a C-class problem can be decomposed. Experiments on an AVIRIS data set for a 12-class problem show significant improvements in classification accuracies while using a much smaller number of features Numéro de notice : A2001-197 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.934070 En ligne : https://ieeexplore.ieee.org/document/934070 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21891
in IEEE Transactions on geoscience and remote sensing > vol 39 n° 7 (July 2001) . - pp 1368 - 1379[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-01071 RAB Revue Centre de documentation En réserve L003 Disponible Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in California / M. Garcia in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
[article]
Titre : Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in California Type de document : Article/Communication Auteurs : M. Garcia, Auteur ; S.L. Ustin, Auteur Année de publication : 2001 Article en page(s) : pp 1480 - 1490 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] analyse spectrale
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] littoral
[Termes IGN] pluie
[Termes IGN] savaneRésumé : (Auteur)Ecosystem responses to interannual weather variability are large and superimposed over any long-term directional climatic responses making it difficult to assign causal relationships to vegetation change. Better understanding of ecosystem responses to interannual climatic variability is crucial to predicting long-term functioning and stability. Hyperspectral data have the potential to detect ecosystem responses that are undetected by broadband sensors and can be used to scale to coarser resolution global mapping sensors, e.g., advanced very high resolution radiometer (AVHRR) and MODIS. This research focused on detecting vegetation responses to interannual climate using the airborne visible-infrared imaging spectrometer (AVIRIS) data over a natural savanna in the Central Coast Range in California. Results of linear spectral mixture analysis and assessment of the model errors were compared for two AVIRIS images acquired in spring of a dry and a wet year. The results show that mean unmixed fractions for these vegetation types were not significantly different between years due to the high spatial variability within the landscape. However, significant community differences were found between years on a pixel basis, underlying the importance of site-specific analysis. Multitemporal hyperspectral coverage is necessary to understand vegetation dynamics. Numéro de notice : A2001-206 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.934079 En ligne : https://doi.org/10.1109/36.934079 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21900
in IEEE Transactions on geoscience and remote sensing > vol 39 n° 7 (July 2001) . - pp 1480 - 1490[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-01071 RAB Revue Centre de documentation En réserve L003 Disponible Discrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery / M. Lewis in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
[article]
Titre : Discrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery Type de document : Article/Communication Auteurs : M. Lewis, Auteur ; V. Joosten, Auteur ; A.A. DE Gasparis, Auteur Année de publication : 2001 Article en page(s) : pp 1471 - 1479 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] airborne multispectral scanner
[Termes IGN] analyse spectrale
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] végétation
[Termes IGN] zone arideNuméro de notice : A2001-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.934078 En ligne : https://doi.org/10.1109/36.934078 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21899
in IEEE Transactions on geoscience and remote sensing > vol 39 n° 7 (July 2001) . - pp 1471 - 1479[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-01071 RAB Revue Centre de documentation En réserve L003 Disponible Georegistration of airborne hyperspectral image data / C. Lee in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
[article]
Titre : Georegistration of airborne hyperspectral image data Type de document : Article/Communication Auteurs : C. Lee, Auteur ; J. Bethel, Auteur Année de publication : 2001 Article en page(s) : pp 1347 - 1351 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] capteur en peigne
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] orthorectificationNuméro de notice : A2001-194 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.934067 En ligne : https://doi.org/10.1109/36.934067 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21888
in IEEE Transactions on geoscience and remote sensing > vol 39 n° 7 (July 2001) . - pp 1347 - 1351[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-01071 RAB Revue Centre de documentation En réserve L003 Disponible A new search algorithm for feature selection in hyperspectral remote sensing images / S.B. Serpico in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)
[article]
Titre : A new search algorithm for feature selection in hyperspectral remote sensing images Type de document : Article/Communication Auteurs : S.B. Serpico, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2001 Article en page(s) : pp 1360 - 1367 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectraleRésumé : (auteur) A new suboptimal search strategy suitable for feature selection in very high-dimensional remote sensing images (e.g., those acquired by hyperspectral sensors) is proposed. Each solution of the feature selection problem is represented as a binary string that indicates which features are selected and which are disregarded. In turn, each binary string corresponds to a point of a multidimensional binary space. Given a criterion function to evaluate the effectiveness of a selected solution, the proposed strategy is based on the search for constrained local extremes of such a function in the above-defined binary space. In particular, two different algorithms are presented that explore the space of solutions in different ways. These algorithms are compared with the classical sequential forward selection and sequential forward floating selection suboptimal techniques, using hyperspectral remote sensing images (acquired by the airborne visible/infrared imaging spectrometer [AVIRIS] sensor) as a data set. Experimental results point out the effectiveness of both algorithms, which can be regarded as valid alternatives to classical methods, as they allow interesting tradeoffs between the qualities of selected feature subsets and computational cost. Numéro de notice : A2001-196 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.934069 En ligne : https://doi.org/10.1109/36.934069 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21890
in IEEE Transactions on geoscience and remote sensing > vol 39 n° 7 (July 2001) . - pp 1360 - 1367[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-01071 RAB Revue Centre de documentation En réserve L003 Disponible Digital image georeferencing from a multiple camera system by GPS-INS / M.M. Mostafa in ISPRS Journal of photogrammetry and remote sensing, vol 56 n° 1 (May - June 2001)PermalinkEtude des relations spécifiques entre végétation et roches du massif de Ronda par télédétection hyperspectrale AVIRIS (1991) et HYMAP (2000) / Guillaume Hallereau (2001)PermalinkEvaluation de la qualité d'une cartographie urbaine à l'aide d'images aériennes à haute résolution / Olivier de Joinville (2001)PermalinkGenauigkeitsuntersuchungen zur GPS/INS-Integration in der Aerophotogrammetrie / Michael Cramer (2001)PermalinkImproving aerial image matching techniques in urban areas using a new true multi-image approach guided from object space / Nicolas Paparoditis (2001)PermalinkEnvironnement et cartographie des camps de refugies au Kenya : une application de la vidéographie aérienne / L. Cambresy in Bulletin du comité français de cartographie, n° 166 (décembre 2000 - février 2001)PermalinkA multi-sensor system for airborne image capture and georeferencing / M.M.R. Mostafa in Photogrammetric Engineering & Remote Sensing, PERS, vol 66 n° 12 (December 2000)PermalinkKnowledge based system for the automatic extraction of road intersections from aerial images / Nicolas Boichis (2000)PermalinkModelling and representation issues in automated feature extraction from aerial and satellite images / Arcot Sowmya in ISPRS Journal of photogrammetry and remote sensing, vol 55 n° 1 (January - February 2000)PermalinkOutils pour la reconstruction automatique de bâtiments à partir d'imagerie aérienne / C. Vestri (2000)Permalink