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Pixel unmixing in hyperspectral data by means of neural networks / Giorgio Licciardi in IEEE Transactions on geoscience and remote sensing, vol 49 n° 11 Tome 1 (November 2011)
[article]
Titre : Pixel unmixing in hyperspectral data by means of neural networks Type de document : Article/Communication Auteurs : Giorgio Licciardi, Auteur ; F. Del Frate, Auteur Année de publication : 2011 Article en page(s) : pp 4163 - 4172 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse en composantes principales
[Termes IGN] classification par réseau neuronal
[Termes IGN] image AHS
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] image PROBA-CHRIS
[Termes IGN] réduction géométrique
[Termes IGN] test de performanceRésumé : (Auteur) Neural networks (NNs) are recognized as very effective techniques when facing complex retrieval tasks in remote sensing. In this paper, the potential of NNs has been applied in solving the unmixing problem in hyperspectral data. In its complete form, the processing scheme uses an NN architecture consisting of two stages: the first stage reduces the dimension of the input vector, while the second stage performs the mapping from the reduced input vector to the abundance percentages. The dimensionality reduction is performed by the so-called autoassociative NNs, which yield a nonlinear principal component analysis of the data. The evaluation of the whole performance is carried out for different sets of experimental data. The first one is provided by the Airborne Hyperspectral Scanner. The second set consists of images from the Compact High-Resolution Imaging Spectrometer on board the Project for On-Board Autonomy satellite, and it includes multiangle and multitemporal acquisitions. The third set is represented by Airborne Visible/InfraRed Imaging Spectrometer measurements. A quantitative performance analysis has been carried out in terms of effectiveness in the dimensionality reduction phase and in terms of the accuracy in the final estimation. The results obtained, when compared with those produced by appropriate benchmark techniques, show the advantages of this approach. Numéro de notice : A2011-445 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2160950 Date de publication en ligne : 01/08/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2160950 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31223
in IEEE Transactions on geoscience and remote sensing > vol 49 n° 11 Tome 1 (November 2011) . - pp 4163 - 4172[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2011111A RAB Revue Centre de documentation En réserve L003 Disponible SVM-based unmixing-to-classification conversion for hyperspectral abundance quantification / F. Mianji in IEEE Transactions on geoscience and remote sensing, vol 49 n° 11 Tome 1 (November 2011)
[article]
Titre : SVM-based unmixing-to-classification conversion for hyperspectral abundance quantification Type de document : Article/Communication Auteurs : F. Mianji, Auteur ; Y. Zhang, Auteur Année de publication : 2011 Article en page(s) : pp 4318 - 4327 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse infrapixellaire
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image hyperspectrale
[Termes IGN] signature spectraleRésumé : (Auteur) Need for a priori knowledge of the components comprising each pixel in a scene has set the endmember determination, rather than the endmember abundance quantification, as the primary focus of many unmixing approaches. In the absence of the information about the pure signatures present in an image scene, which is often the case, the mean spectra of the pixel vectors, directly extracted from the scene, are usually used as the pure signatures' spectra. This approach which is mathematically optimized for unmixing problems with a priori known information ignores some statistical properties of the extracted samples and leads to a suboptimal solution for real situations. This paper proposes a novel learning-based unmixing-to-classification conversion model to treat the abundance quantification task as a classification problem. Support vector machine, as an efficient classifier, is used to realize this model. It exploits the statistical nature (endmember spectral variability) of the extracted endmember representatives from the hyperspectral scene, rather than solving the problem according to the ideal model in which only the mean spectra of each training sample set is used. Several experiments are carried out on simulated and real hyperspectral images. The obtained results validate the high performance of the proposed technique in abundance quantification which is a key subpixel information detection capability. Numéro de notice : A2011-446 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2166766 Date de publication en ligne : 06/10/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2166766 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31224
in IEEE Transactions on geoscience and remote sensing > vol 49 n° 11 Tome 1 (November 2011) . - pp 4318 - 4327[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2011111A RAB Revue Centre de documentation En réserve L003 Disponible A volumetric approach to population estimation using lidar remote sensing / Zhong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 11 (November 2011)
[article]
Titre : A volumetric approach to population estimation using lidar remote sensing Type de document : Article/Communication Auteurs : Zhong Lu, Auteur ; J. Im, Auteur ; L. Quackenbush, Auteur Année de publication : 2011 Article en page(s) : pp 1145 - 1156 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Denver
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] estimation statistique
[Termes IGN] habitat urbain
[Termes IGN] ilot
[Termes IGN] lasergrammétrie
[Termes IGN] population urbaine
[Termes IGN] recensement démographique
[Termes IGN] régression
[Termes IGN] volume (grandeur)
[Termes IGN] zone urbaineRésumé : (Auteur) This research investigated the applicability of lidar data for estimating population at the census block level using a volumetric approach. The study area, near the urban downtown area of Denver, Colorado, was selected since it includes dense distribution of different types of residential buildings. A modified morphological building detection algorithm was proposed to extract buildings from the lidar-derived surfaces. The extraction results showed that the modified morphological building detection algorithm can effectively recover building pixels occluded by nearby trees. The extracted buildings were further refined to residential buildings using parcel data. Two approaches (i.e., area- and volume-based) to population estimation were investigated at the census block level. Four regression models (i.e., simple linear regression, multiple linear regression, regression tree using one variable, and regression tree using multiple variables) were used to identify the relationship between census population and the area or volume information of the residential buildings. The volume-based models over-whelmingly outperformed the area-based models in the study area, and the models using multiple variables yielded more accurate estimation than the single variable models. The volume-based regression tree model using multiple variables yielded the most accurate estimations: R2 = 0.89, RMSE = 21 people, and RRMSE = 26.8 percent in the calibration site; and R2 = 0.80, RMSE = 27 people, and RRMSE = 30.1 percent in the validation site. As the results show, the volumetric approach using lidar remote sensing is effective for population estimation in regions with heterogeneous housing characteristics. Numéro de notice : A2011-448 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.77.11.1145 En ligne : https://doi.org/10.14358/PERS.77.11.1145 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31226
in Photogrammetric Engineering & Remote Sensing, PERS > vol 77 n° 11 (November 2011) . - pp 1145 - 1156[article]Surveying buildings: Point clouds and multi-image panoramas / Luigi Colombo in Geoinformatics, vol 14 n° 7 (01/10/2011)
[article]
Titre : Surveying buildings: Point clouds and multi-image panoramas Type de document : Article/Communication Auteurs : Luigi Colombo, Auteur ; Barbara Marana, Auteur Année de publication : 2011 Article en page(s) : pp 26 - 28 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image terrestre
[Termes IGN] lasergrammétrie
[Termes IGN] Lombardie
[Termes IGN] modélisation 3D
[Termes IGN] monument historique
[Termes IGN] photogrammétrie terrestre
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de points
[Termes IGN] surveillance d'ouvrage
[Termes IGN] texture d'imageRésumé : (Auteur) The development of building knowledge systems is nowadays a meaningful step when planning architectural maintenance and managing emergencies during a building's life cycle. A 3D photo-textured model, which can describe both spatial connections and material properties, is a measurable virtual object that is achieved via terrestrial survey techniques, such as laser scanning and imaging. This article presents the current status of techniques and technologies for the construction of a textured model, through the support of experiences regarding an ancient historical building in the Lombardy region of Northern Italy. Numéro de notice : A2011-422 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31201
in Geoinformatics > vol 14 n° 7 (01/10/2011) . - pp 26 - 28[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 262-2011071 SL Revue Centre de documentation Revues en salle Disponible Building footprint database improvement for 3D reconstruction: A split and merge approach and its evaluation / Bruno Vallet in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 5 (September - October 2011)
[article]
Titre : Building footprint database improvement for 3D reconstruction: A split and merge approach and its evaluation Type de document : Article/Communication Auteurs : Bruno Vallet , Auteur ; Marc Pierrot-Deseilligny , Auteur ; Didier Boldo , Auteur ; Mathieu Brédif , Auteur Année de publication : 2011 Article en page(s) : pp 732 - 742 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] base de données thématiques
[Termes IGN] bati
[Termes IGN] données vectorielles
[Termes IGN] empreinte
[Termes IGN] modèle numérique de surface
[Termes IGN] polygone
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] segmentation d'image
[Termes IGN] zone urbaineRésumé : (Auteur) We present a general framework to improve a vectorial building footprint database consisting of a set of 2D polygons. The aim of this improvement is to make the database more proper to subsequent 3D building reconstruction at a large scale. Each polygon is split into several simple polygons guided by a digital elevation model (DEM). We say that this segmentation is vectorial as we produce segmentations that intrinsically have simple polygonal shapes, instead of doing a raster segmentation of the DEM within the polygon then trying to simplify it in a vectorization step. The method is based on a Mumford and Shah like energy functional characterizing the quality of the segmentation. We simplify the problem by imposing that the segmentation edges have directions present in the input polygon over which the DEM is defined. We evaluate the validity of the proposed method on a very large dataset and discuss its pros and cons based on this evaluation. Numéro de notice : A2011-408 Affiliation des auteurs : MATIS (1993-2011) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2011.06.005 Date de publication en ligne : 29/07/2011 En ligne : https://doi.org/10.1016/j.isprsjprs.2011.06.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31187
in ISPRS Journal of photogrammetry and remote sensing > vol 66 n° 5 (September - October 2011) . - pp 732 - 742[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2011051 SL Revue Centre de documentation Revues en salle Disponible Ondelettes et théorie des évidences pour la classification orientée-objet : Caractérisation et suivi des changements d’occupation des sols de la métropole de Rennes / A. Lefebvre in Revue internationale de géomatique, vol 21 n° 3 (septembre - novembre 2011)PermalinkSeismic-zonation of Port-au-Prince using pixel- object-based imaging analysis methods on Aster GDEM / S. Yong in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 9 (September 2011)PermalinkEmpirical comparison of full-waveform Lidar algorithms: range extraction and discrimination performance / C. 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Shu in Marine geodesy, vol 33 n° 2-3 (April - September 2010)PermalinkLand use and land cover change detection using satellite remote sensing techniques in the mountainous Three Gorges Area, China / Z. Chen in International Journal of Remote Sensing IJRS, vol 31 n° 6 (March 2010)PermalinkSampling approaches for one-pass land-use/land-cover change mapping / Zhi Huang in International Journal of Remote Sensing IJRS, vol 31 n° 6 (March 2010)PermalinkAn improved segmentation approach for planar surfaces from undestructured 3D point clouds / T.M. Awwad in Photogrammetric record, vol 25 n° 129 (March - May 2010)PermalinkLand-cover change detection using one-class support vector machine / P. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 3 (March 2010)PermalinkObject-based image analysis: definiens' egognition server software / E. 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Royer (2010)Permalink