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3D building modelling with digital map, Lidar data and video image sequences / Y. Zhang in Photogrammetric record, vol 20 n° 111 (September - November 2005)
[article]
Titre : 3D building modelling with digital map, Lidar data and video image sequences Type de document : Article/Communication Auteurs : Y. Zhang, Auteur ; Z. Zhang, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 285 - 302 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] aérotriangulation
[Termes IGN] capteur aérien
[Termes IGN] compensation par faisceaux
[Termes IGN] élément d'orientation externe
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modélisation 3D
[Termes IGN] orthoimage
[Termes IGN] texture d'imageRésumé : (Auteur) Three-dimensional (3D) reconstruction and texture mapping of buildings or other man-made objects are key aspects for 3D city landscapes. An effective coarse-to-fine approach for 3D building model generation and texture mapping based on digital photogrammetric techniques is proposed. Three video image sequences, two oblique views of building walls and one vertical view of building roofs, acquired by a digital video camera mounted on a helicopter are used as input images. Lidar data and a coarse two-dimensional (2D) digital vector map used for car navigation are also used as information sources. Automatic aerial triangulation (AAT) suitable for a high overlap image sequence is used to give initial values of camera parameters of each image. To obtain accurate image lines, the correspondence between outlines of the building and their line-features in the image sequences is determined with a coarse-to-fine strategy. A hybrid point/line bundle adjustment is used to ensure the stability and accuracy of reconstruction. Reconstructed buildings with fine textures superimposed on a digital elevation model (DEM) and ortho-image are realistically visualised. Experimental results show that the proposed approach of 3D city model generation has a promising future in many applications. Numéro de notice : A2005-381 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2005.00316.x En ligne : https://doi.org/10.1111/j.1477-9730.2005.00316.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27517
in Photogrammetric record > vol 20 n° 111 (September - November 2005) . - pp 285 - 302[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-05031 RAB Revue Centre de documentation En réserve L003 Disponible 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 Radial basis function neural networks classification using very high spatial resolution satellite imagery: an application to the habitat area of Lake Kerkini (Greece) / Iphigenia Keramitsoglou in International Journal of Remote Sensing IJRS, vol 26 n° 9 (May 2005)
[article]
Titre : Radial basis function neural networks classification using very high spatial resolution satellite imagery: an application to the habitat area of Lake Kerkini (Greece) Type de document : Article/Communication Auteurs : Iphigenia Keramitsoglou, Auteur ; H. Sarimveis, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1861 - 1880 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse texturale
[Termes IGN] bande spectrale
[Termes IGN] classificateur paramétrique
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] fonction de base radiale
[Termes IGN] Grèce
[Termes IGN] image à très haute résolution
[Termes IGN] lacRésumé : (Auteur) This study investigates the potential of applying the radial basis function (RBF) neural network architecture for the classification of multispectral very high spatial resolution satellite images into 13 classes of various scales. For the development of the RBF classifiers, the innovative fuzzy means training algorithm is utilized, which is based on a fuzzy partition of the input space. The method requires only a short amount of time to select both the structure and the parameters of the RBF classifier. The new technique was applied to the area of Lake Kerkini, which is a wetland of great ecological value, located in northern Greece. Eleven experiments were carried out in total in order to investigate the performance of the classifier using different input parameters (spectral and textural) as well as different window sizes and neural network complexities. For comparison purposes the same satellite scene was classified using the maximum likelihood (MLH) classification with the same set of training samples. Overall, the neural network classifiers outperformed the MLH classification by 10-17%, reaching a maximum overall accuracy of 78%. Analysis showed that the selection of input parameters is vital for the success of the classifiers. On the other hand, the incorporation of textural analysis and/or modification of the window size do not affect the performance substantially. Numéro de notice : A2005-255 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331326594 En ligne : https://doi.org/10.1080/01431160512331326594 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27391
in International Journal of Remote Sensing IJRS > vol 26 n° 9 (May 2005) . - pp 1861 - 1880[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt A comparison of local variance, fractal dimension, and Moran's index as aids to multispectral image classification / C.W. Emerson in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)
[article]
Titre : A comparison of local variance, fractal dimension, and Moran's index as aids to multispectral image classification Type de document : Article/Communication Auteurs : C.W. Emerson, Auteur ; N. Siu-Ngan Lam, Auteur ; D.A. Quattrochi, Auteur Année de publication : 2005 Article en page(s) : pp 1575 - 1588 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] Atlanta (Géorgie)
[Termes IGN] autocorrélation spatiale
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] ERDAS Imagine
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multibande
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] segmentation d'image
[Termes IGN] texture d'imageRésumé : (Auteur) The accuracy of traditional multispectral maximum-likelihood image classification is limited by the multi-modal statistical distributions of digital numbers from the complex, heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery with the goal of improving urban land cover classification accuracy. Tools available in the ERDAS Imagine™ software package and the Image Characterization and Modeling System (ICAMS) were used to analyse Landsat ETM+ imagery of Atlanta, Georgia. Images were created from the ETM+ panchromatic band using the three texture indices. These texture images were added to the stack of multispectral bands and classified using a supervised, maximum likelihood technique. Although each texture band improved the classification accuracy over a multispectral only effort, the addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques. Numéro de notice : A2005-204 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331326765 En ligne : https://doi.org/10.1080/01431160512331326765 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27341
in International Journal of Remote Sensing IJRS > vol 26 n° 8 (April 2005) . - pp 1575 - 1588[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05081 RAB Revue Centre de documentation En réserve L003 Exclu du prêt 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
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Code-barres Cote Support Localisation Section Disponibilité 065-05042 RAB Revue Centre de documentation En réserve L003 Disponible Updating a digital geographic database using Vehicle-borne Laser scanners and line cameras / H. Zhao in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 4 (April 2005)PermalinkThe utility of texture analysis to improve per-pixel classification for high to very high spatial resolution imagery / Anne Puissant in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)PermalinkPerformance of different spectral and textural photograph features in multi-source forest inventory / Sakari Tuominen in Remote sensing of environment, vol 94 n° 2 (30/01/2005)Permalink3D building facade reconstruction under mesh form from multiple wide angle views / Lionel Pénard (2005)PermalinkImage Analysis, 14th Scandinavian Conference, SCIA 2005, Joensuu, Finland, June 2005 / Heikki Kalviainen (2005)PermalinkIntérêt de la fusion d'images à haute résolution spatiale pour la classification de l'occupation du sol en milieu urbain / Yves Cornet in Revue internationale de géomatique, vol 14 n° 3 - 4 (septembre 2004 – février 2005)PermalinkAutomatic change detection by evidential fusion of change indices / Sylvie Le Hégarat-Mascle in Remote sensing of environment, vol 91 n° 3 (30/06/2004)PermalinkExamining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case / D. Chen in International Journal of Remote Sensing IJRS, vol 25 n° 11 (June 2004)PermalinkÉtude de l'extension du bâti sur le littoral sénégalais à partir des paramètres texturaux de Haralick / G. Ackermann in Revue Française de Photogrammétrie et de Télédétection, n°173-174 (Juin 2004)PermalinkEvaluation comparative en cartographie forestière de l'analyse de texture et de la transformée en paquets d'ondelettes par le moyen d'un classifieur / A. Hammouch in Photo interprétation, vol 40 n° 1 (Mars 2004)Permalink