IEEE Transactions on geoscience and remote sensing / IEEE Geoscience and remote sensing society (Etats-Unis) . vol 43 n° 4Paru le : 01/04/2005 |
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Ajouter le résultat dans votre panierIntegration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data / L.O. Jimenez in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)
[article]
Titre : Integration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data Type de document : Article/Communication Auteurs : L.O. Jimenez, Auteur ; J.L. Rivera-Medina, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 844 - 851 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multivariée
[Termes IGN] classification contextuelle
[Termes IGN] classification non dirigée
[Termes IGN] classification orientée objet
[Termes IGN] extraction automatique
[Termes IGN] image à haute résolution
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] intégration de données
[Termes IGN] objet homogèneRésumé : (Auteur) This paper presents a method of unsupervised enhancement of pixels homogeneity in a local neighborhood. This mechanism will enable an unsupervised contextual classification of multispectral data that integrates the spectral and spatial information producing results that are more meaningful to the human analyst. This unsupervised classifier is an unsupervised development of the well-known supervised extraction and classification for homogenous objects (ECHO) classifier. One of its main characteristics is that it simplifies the retrieval process of spatial structures. This development is specially relevant for the new generation of airborne and spaceborne sensors with high spatial resolution. Numéro de notice : A2005-192 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.843193 En ligne : https://doi.org/10.1109/TGRS.2004.843193 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27329
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 4 (April 2005) . - pp 844 - 851[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05042 RAB Revue Centre de documentation En réserve L003 Disponible Use of the Bradley-Terry model to quantify association in remotely sensed images / Alfred Stein in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)
[article]
Titre : Use of the Bradley-Terry model to quantify association in remotely sensed images Type de document : Article/Communication Auteurs : Alfred Stein, Auteur ; J. Aryal, Auteur ; G. Gort, Auteur Année de publication : 2005 Article en page(s) : pp 852 - 856 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification barycentrique
[Termes IGN] classification par la distance de Mahalanobis
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] estimation de précision
[Termes IGN] estimation des paramètres
[Termes IGN] image Ikonos
[Termes IGN] image Terra-ASTER
[Termes IGN] Pays-BasRésumé : (Auteur) Thematic maps prepared from remotely sensed images require a statistical accuracy assessment. For this purpose, the k-statistic is often used. This statistic does not distinguish between whether one unit is classified as another, or vice versa. In this paper, the Bradley-Terry (BT) model is applied for accuracy assessment. This model compares categories pairwise. The probability of one class over another class is estimated as well as the expected values of class pixels. The study is illustrated with an Advanced Spaceborne Thermal Emission and Reflection Radiometer image from the Netherlands, to which a maximum-likelihood classification with the Euclidean distance is applied. An error matrix is generated using an IKONOS image from the same area as ground truth. It is shown to which degree the BT model extends the K-statistic. A comparison with the Mahalanobis distance is made. Standardization is carried out to overcome problems emerging from the fact that a common BT model does not include the number of correctly classified pixels. The study shows how the BT model serves as an alternative to the usual k-statistic. Numéro de notice : A2005-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.843569 En ligne : https://doi.org/10.1109/TGRS.2005.843569 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27330
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 4 (April 2005) . - pp 852 - 856[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05042 RAB Revue Centre de documentation En réserve L003 Disponible An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images / Y. Bazi in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)
[article]
Titre : An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images Type de document : Article/Communication Auteurs : Y. Bazi, Auteur ; Lorenzo Bruzzone, Auteur ; F. Melgani, Auteur Année de publication : 2005 Article en page(s) : pp 874 - 887 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] chatoiement
[Termes IGN] détection de changement
[Termes IGN] distribution de Gauss
[Termes IGN] filtrage numérique d'image
[Termes IGN] image ERS-SAR
[Termes IGN] image multitemporelle
[Termes IGN] image radar
[Termes IGN] seuillage d'imageRésumé : (Auteur) In this paper, we present a novel automatic and unsupervised change-detection approach specifically oriented to the analysis of multitemporal single-channel single-polarization synthetic aperture radar (SAR) images. This approach is based on a closed-loop process made up of three main steps: 1) a novel preprocessing based on a controlled adaptive iterative filtering; 2) a comparison between multitemporal images carried out according to a standard log-ratio operator; and 3) a novel approach to the automatic analysis of the log-ratio image for generating the change-detection map. The first step aims at reducing the speckle noise in a controlled way in order to maximize the discrimination capability between changed and unchanged classes. In the second step, the two filtered multitemporal images are compared to generate a log-ratio image that contains explicit information on changed areas. The third step produces the change-detection map according to a thresholding procedure based on a reformulation of the Kittler-Illingworth (KI) threshold selection criterion. In particular, the modified KI criterion is derived under the generalized Gaussian assumption for modeling the distributions of changed and unchanged classes. This parametric model was chosen because it is capable of better fitting the conditional densities of classes in the log-ratio image. In order to control the filtering step and, accordingly, the effects of the filtering process on change-detection accuracy, we propose to identify automatically the optimal number of despeckling filter iterations [Step 1)] by analyzing the behavior of the modified KI criterion. This results in a completely automatic and self-consistent change-detection approach that avoids the use of empirical methods for the selection of the best number of filtering iterations. Experiments carried out on two sets of multitemporal images (characterized by different levels of speckle noise) acquired by the European Remote Sensing 2 satellite SAR sensor confirm the effectiveness of the proposed unsupervised approach, which results in change-detection accuracies very similar to those that can be achieved by a manual supervised thresholding. Numéro de notice : A2005-194 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.842441 En ligne : https://doi.org/10.1109/TGRS.2004.842441 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27331
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 4 (April 2005) . - pp 874 - 887[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-05042 RAB Revue Centre de documentation En réserve L003 Disponible