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Auteur Alfred Stein |
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Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty / Arko Lucieer in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)
[article]
Titre : Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty Type de document : Article/Communication Auteurs : Arko Lucieer, Auteur ; Alfred Stein, Auteur ; Peter F. Fisher, Auteur Année de publication : 2005 Article en page(s) : pp 2917 - 2936 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multivariée
[Termes IGN] extraction automatique
[Termes IGN] image CASI
[Termes IGN] image multibande
[Termes IGN] incertitude des données
[Termes IGN] niveau de gris (image)
[Termes IGN] objet géographique
[Termes IGN] segmentation d'image
[Termes IGN] texture d'imageRésumé : (Auteur) In this study, a segmentation procedure is proposed, based on grey-level and multivariate texture to extract spatial objects from an image scene. Object uncertainty was quantified to identify transitions zones of objects with indeterminate boundaries. The Local Binary Pattern (LBP) operator, modelling texture, was integrated into a hierarchical splitting segmentation to identifiy homogeneous texture regions in an image. We proposed a multivariate extension of the standard univariate LBP operator to describe colour texture. The paper is illustrated with two case studies. The first considers an image with a composite of texture regions. The two LBP operators provided good segmentation results on both grey-scale and colour textures, depicted by accuracy values of 96% and 98% respectively. The second case study involved segmentation of coastal land cover objects from a multispectral Compact Airborne Spectral Imager (CASI) image, of a coastal area in the UK. Segmentation based on the univariate LBP measure provided unsatisfactory segmentation results from a single CASI band (70% accuracy). A multivariate LBP-based segmentation of three CASI bands improved segmentation results considerably (77% accuracy). Uncertainty values for object building blocks provided valuable information for identification of object transition zones. We conclude that the multivariate LBP texture model in combinaison with a hierarchical splitting segmentation framework is suitable for identifying objects and for quantifying their uncertainty. Numéro de notice : A2005-294 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500057723 En ligne : https://doi.org/10.1080/01431160500057723 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27430
in International Journal of Remote Sensing IJRS > vol 26 n° 14 (July 2005) . - pp 2917 - 2936[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 080-05141 RAB Revue Centre de documentation En réserve L003 Exclu du prêt 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 Integrating interferometric SAR data with levelling measurements of land subsidence using geostatistic / Y. Zhou in International Journal of Remote Sensing IJRS, vol 24 n° 18 (September 2003)
[article]
Titre : Integrating interferometric SAR data with levelling measurements of land subsidence using geostatistic Type de document : Article/Communication Auteurs : Y. Zhou, Auteur ; Alfred Stein, Auteur ; Martien Molenaar, Auteur Année de publication : 2003 Article en page(s) : pp 3547 - 3563 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bruit blanc
[Termes IGN] Chine
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données de terrain
[Termes IGN] eau souterraine
[Termes IGN] erreur
[Termes IGN] erreur moyenne quadratique
[Termes IGN] extraction du sursol
[Termes IGN] géostatistique
[Termes IGN] image radar moirée
[Termes IGN] intégration de données
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] krigeage
[Termes IGN] nivellement
[Termes IGN] précision centimétrique
[Termes IGN] subsidence
[Termes IGN] variogrammeRésumé : (Auteur) Differential Synthetic Aperture Radar (SAR) interferometric (D-InSAR) data of ground surface deformation are affected by several error sources associated with image acquisitions and data processing. In this paper, we study the use of D-InSAR for quantifying land subsidence due to groundwater extraction. We model the data as the sum of a trend, a zeromean stochastic process and white noise. A geostatistical approach combines D-InSAR subsidence data with in situ levelling measurements. The objective of this paper is to correct the errors contained in the D-InSAR measurements by using measurements as the ground data to improve their accuracy. Discrepancies between the true subsidence values and original D-InSAR measurements are analysed at levelling points using variograms and predicted at unvisited points using kriging. The integrated measurements are obtained by subtracting the predicted errors from the original D-InSAR measurements. The proposed method is applied to data collected in the Tianjin (China) area where land subsidence occurs due to groundwater extraction. Results demonstrate the capability of the D-InSAR technique for detecting subsidence at the centimetre level, and of using a limited number of levelling points to improve the accuracy of D-InSAR deformation measurements provided the coherence of images used is high enough. Discrepancies between the true subsidence values and D-InSAR measurements are quantified using the root mean square error (RMSE). RMSE for the original data was equal to 2.8, and 0.8 for the integrated data, whereas the mean error was equal to 2.1 and 0.0, respectively. Numéro de notice : A2003-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116021000023880 En ligne : https://doi.org/10.1080/0143116021000023880 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22557
in International Journal of Remote Sensing IJRS > vol 24 n° 18 (September 2003) . - pp 3547 - 3563[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-03181 RAB Revue Centre de documentation En réserve L003 Disponible