Descripteur
Documents disponibles dans cette catégorie (302)
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
Active-metric learning for classification of remotely sensed hyperspectral images / Edoardo Pasolli in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)
[article]
Titre : Active-metric learning for classification of remotely sensed hyperspectral images Type de document : Article/Communication Auteurs : Edoardo Pasolli, Auteur ; Hsiuhan Lexie Yang, Auteur ; Melba M. Crawford, Auteur Année de publication : 2016 Article en page(s) : pp 1925 - 1939 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiquesRésumé : (Auteur) Classification of remotely sensed hyperspectral images via supervised approaches is typically affected by high dimensionality of the spectral data and a limited number of labeled samples. Dimensionality reduction via feature extraction and active learning (AL) are two approaches that researchers have investigated independently to deal with these two problems. In this paper, we propose a new method in which the feature extraction and AL steps are combined into a unique framework. The idea is to learn and update a reduced feature space in a supervised way at each iteration of the AL process, thus taking advantage of the increasing labeled information provided by the user. In particular, the computation of the reduced feature space is based on the large-margin nearest neighbor (LMNN) metric learning principle. This strategy is applied in conjunction with k-nearest neighbor ( k-NN) classification, for which a new sample selection strategy is proposed. The methodology is validated experimentally on four benchmark hyperspectral data sets. Good improvements in terms of classification accuracy and computational time are achieved with respect to the state-of-the-art strategies that do not combine feature extraction and AL. Numéro de notice : A2016-836 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2490482 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2490482 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82880
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 4 (April 2016) . - pp 1925 - 1939[article]Fusion of hyperspectral images and digital surface models for urban object extraction / Janja Avbelj (2016)
Titre : Fusion of hyperspectral images and digital surface models for urban object extraction Type de document : Thèse/HDR Auteurs : Janja Avbelj, Auteur ; Xiaoxiang Zhu, Directeur de thèse Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2016 Collection : DGK - C, ISSN 0065-5325 num. 771 Importance : 143 p. ISBN/ISSN/EAN : 978-3-7696-5183-6 Note générale : bibliographie
PhD DissertationLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] classification bayesienne
[Termes IGN] détection d'objet
[Termes IGN] extraction automatique
[Termes IGN] fusion de données
[Termes IGN] image hyperspectrale
[Termes IGN] modèle numérique de surface
[Termes IGN] optimisation (mathématiques)
[Termes IGN] polygone
[Termes IGN] rectangle englobant minimumRésumé : (auteur) Buildings are prominent objects of the constantly changing urban environment. Accurate and up to date Building Polygons (BP) are needed for a variety of applications, e.g. 3D city visualisation, micro climate forecast, and real estate databases. The increasing number of earth observation remote sensing images enables the development of methods for building extraction. For instance, Hyperspectral Images (HSI) are a source of information about the material of the objects in the scene, whereas the Digital Surface Models (DSM) carry information about height of the surface and of objects. Thus, complementary information from multi-modal images, such as HSI and DSM, is needed to provide better understanding of the observed objects. A variation in material and height is represented by an edge in HSI and DSM, respectively. Edges in an image carry large portions of information about the geometry of the objects, because they delineate the boundaries between them. Object extraction and delineation is more reliable if information content from HSI, DSM, and edge information is jointly accounted for. The focus in this thesis is on method development for BP extraction using complementary information from HSI and DSM by accounting for edge information. Furthermore, a new quality measure, which accounts for shape differences and geometric accuracy between extracted and reference polygons, is proposed. Object and edge detection from an image is meaningful only for some range of scales. Edge detection in scale space is motivated by showing that in the same image different edges appear at different scales. Instead of deterministic edge detection, edge probabilities are computed in a linear scale space. Bayesian fusion of edge probabilities is proposed, which employs a Gaussian mixture model. The scale, at which an edge probability is computed, is defined by a confidence probability. The impact of selecting mixing coefficients in the Gaussian mixture model according to a prior knowledge or by a fully automatic data-driven approach is investigated. Main limitations of joining the edge probabilities from different datasets are the coregistration between the datasets and the inaccuracies in the datasets. The rectilinear BP are adjusted by means of weighted least squares, where the weights are defined on the basis of joint edge probabilities. Two mathematical models for rectilinear BP are proposed, one with a strict rectilinearity constraint and the second one, which introduces a relaxed rectilinearity constraint through weighting. The experiments on synthetic images show that the model with strict constraint gives better results, if the BP under consideration are all rectilinear. Otherwise, the relaxed rectilinearity constraint through weighting balances better between the rectilinearity assumption and fitness to the data. The approximate BP are created by a Minimum Bounding Rectangle (MBR) method. A main contribution of the proposed iterative MBR method is the automatic selection of a level of complexity of MBR through analysis of a cost function. A metric for comparison of polygons and line segments, named PoLiS metric, is defined. It compares polygons with different number of vertices, is insensitive to the number of vertices on polygon's edges, is monotonic, and has a nearly linear response to small changes in translation, rotation, and scale. Its characteristics are discussed and compared to the commonly used measures for BP evaluation. In all experiments the BP are evaluated by computing the newly proposed PoLiS metric and quality rate. The feasibility of joining all the proposed methods in one workflow is shown through the experiment, which is carried out on 17 HSI-DSM dataset pairs with four different ground sampling distances. The main finding of the experiment is that joining the information from multi-modal images, i.e. HSI and DSM, results in better quality of the adjusted BP. For instance, even for datasets with 4 m ground sampling distance, the completeness, correctness and quality rate values of extracted BP are better than 0.83, 0.68, and 0.60. Inaccuracies of the images, such as holes in DSM or imperfect DSM for 1151 orthorectification, are influencing the accuracy and localisation of edge probabilities and consequently also the accuracy of adjusted BP. Note de contenu : bibliographie Numéro de notice : 19792 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Dissertation : Photogrammetry : Stuttgart : 2016 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85016 Documents numériques
en open access
Fusion of Hyperspectral Images and Digital Surface Models for Urban Object ExtractionAdobe Acrobat PDF Mise en place de procédures automatiques en vue d’accélérer la production des plans topographiques au sein de l’entreprise Techni Drone / Kévin Javerliat (2016)
Titre : Mise en place de procédures automatiques en vue d’accélérer la production des plans topographiques au sein de l’entreprise Techni Drone Type de document : Mémoire Auteurs : Kévin Javerliat, Auteur Editeur : Strasbourg : Institut National des Sciences Appliquées INSA Strasbourg Année de publication : 2016 Importance : 43 p. Format : 21 x 30 cm Note générale : Bibliographie
Mémoire de fin d'études INSA StrasbourgLangues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] acquisition d'images
[Termes IGN] analyse comparative
[Termes IGN] chaîne de traitement
[Termes IGN] classification automatique
[Termes IGN] drone
[Termes IGN] extraction automatique
[Termes IGN] image aérienne
[Termes IGN] ligne de rupture de pente
[Termes IGN] logiciel de photogrammétrie
[Termes IGN] orthoimage
[Termes IGN] plan topographique
[Termes IGN] point de vérification
[Termes IGN] Python (langage de programmation)
[Termes IGN] QGIS
[Termes IGN] semis de points
[Termes IGN] traitement de semis de pointsIndex. décimale : INSAS Mémoires d'ingénieur de l'INSA Strasbourg - Topographie, ex ENSAIS Résumé : (Auteur) Ce projet au sein d’une entreprise spécialisée dans l’utilisation des drones civils m’a permis de me familiariser avec les processus d’acquisition des données acquises par drone. Il m’apporte une expérience pratique dans un domaine en plein essor et plus largement en photogrammétrie. Plus largement, j’ai pu développer mes compétences dans le domaine de la programmation en langage Python. Ce stage a également été l’occasion d’explorer les fonctionnalités de nouveaux logiciels tels que QGIS, Pix4D Mapper ou Mensura Genius. Enfin, j’ai une vision du travail de l’ingénieur topographe en dehors d’un cabinet de géomètres. Plus généralement, ce stage a été l’occasion de découvrir le fonctionnement d’une société autre qu’un cabinet de géomètres experts mêlant des personnes aux compétences totalement différentes dans des domaines très variés. Note de contenu : INTRODUCTION
1. PRÉSENTATION DE TECHNI DRONE ET DE SON FONCTIONNEMENT GÉNÉRAL
1.1. Présentation de la société
1.2. Le matériel utilisé
1.3. Le fonctionnement général d’une prestation
2. LA CHAÎNE DE TRAITEMENT
2.1. L’élaboration de l’état de la chaîne de traitement
2.2. Les conclusions de l’état de la chaîne de traitement
3. COMPARATIF DES SOLUTIONS DE TRAITEMENT PHOTOGRAMMÉTRIQUE
3.1. Les fonctionnalités indispensables aux solutions de traitement photogrammétrique
3.2. La réponse des solutions de traitement à nos exigences
3.3. Le choix de la solution de traitement photogrammétrique
4. EXTRACTION AUTOMATIQUE DES POINTS DE CONTRÔLE
4.1. L’état de l’art
4.2. La solution envisagée chez Techni Drone
4.3. Conclusion et perspectives
5. L’EXTRACTION AUTOMATIQUE DES LIGNES DE RUPTURE DE PENTE
6. L’EXTENSION SOUS QGIS
6.1. Présentation de QGIS, Python et les extensions
6.2. La classification des lignes de rupture de pente
6.3. La réalisation du plan des stocks
6.4. L’élaboration du diagnostic des pistes
6.5. Conclusion sur l’extension créée
7. LES AMÉLIORATIONS ORGANISATIONNELLES
7.1. La disponibilité de Mensura Genius
7.2. La mise en réseau des postes
7.3. Le suivi des traitements en cours
8. LES APPORTS DE LA NOUVELLE CHAÎNE DE TRAITEMENT
9. LES ÉVOLUTIONS NÉCESSAIRES POUR OBTENIR UN SERVICE DE TYPE « CLOUD »
9.1. Présentation du projet
9.2. La diffusion des données sur le web
CONCLUSION ET PERSPECTIVESNuméro de notice : 22694 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Mémoire ingénieur INSAS Organisme de stage : TECHNI DRONE Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84831 Documents numériques
Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation / Fateme Ameri in Photogrammetric record, vol 30 n° 152 (December 2015 - February 2016)
[article]
Titre : Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation Type de document : Article/Communication Auteurs : Fateme Ameri, Auteur ; Mohammad Javad Valadan Zoej, Auteur Année de publication : 2015 Article en page(s) : pp 363 - 386 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification automatique d'objets
[Termes IGN] extraction automatique
[Termes IGN] extraction du réseau routier
[Termes IGN] image aérienne
[Termes IGN] image Ikonos
[Termes IGN] image Quickbird
[Termes IGN] optimisation par essaim de particules
[Termes IGN] réseau routier
[Termes IGN] vectorisationRésumé : (auteur) This paper introduces an innovative automatic road-vectorisation algorithm based on dynamic pixel clustering using particle swarm optimisation. A new cost function is designed to optimise the number and position of road keypoints and is capable of deriving road centrelines without considering geometric, spectral or topological characteristics in the road model. The algorithm is applied to different high-resolution images (IKONOS, QuickBird and aerial photographs) and is evaluated with respect to RMSE, correctness and completeness. Moreover, a new quality parameter is defined to evaluate a “kinking” effect in roads. Extraction of different road shapes with an acceptable precision in both urban and rural environments proves the efficiency of the algorithm in yielding complete road networks. Numéro de notice : A2015-827 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12123 Date de publication en ligne : 15/12/2015 En ligne : https://doi.org/10.1111/phor.12123 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79123
in Photogrammetric record > vol 30 n° 152 (December 2015 - February 2016) . - pp 363 - 386[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 106-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
[article]
Titre : Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching Type de document : Article/Communication Auteurs : Amin Sedaghat, Auteur ; Hamid Ebadi, Auteur Année de publication : 2015 Article en page(s) : pp 62 – 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] extraction automatique
[Termes IGN] image Geoeye
[Termes IGN] image IRS
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multicapteur
[Termes IGN] image Quickbird
[Termes IGN] image SPOT 4
[Termes IGN] image SPOT 5
[Termes IGN] image SPOT 6
[Termes IGN] image Terra-ASTER
[Termes IGN] image Worldview
[Termes IGN] invariant
[Termes IGN] SIFT (algorithme)Résumé : (auteur) Robust, well-distributed and accurate feature matching in multi-sensor remote sensing image is a difficult task duo to significant geometric and illumination differences. In this paper, a robust and effective image matching approach is presented for multi-sensor remote sensing images. The proposed approach consists of three main steps. In the first step, UR-SIFT (Uniform robust scale invariant feature transform) algorithm is applied for uniform and dense local feature extraction. In the second step, a novel descriptor namely Distinctive Order Based Self Similarity descriptor, DOBSS descriptor, is computed for each extracted feature. Finally, a cross matching process followed by a consistency check in the projective transformation model is performed for feature correspondence and mismatch elimination. The proposed method was successfully applied for matching various multi-sensor satellite images as: ETM+, SPOT 4, SPOT 5, ASTER, IRS, SPOT 6, QuickBird, GeoEye and Worldview sensors, and the results demonstrate its robustness and capability compared to common image matching techniques such as SIFT, PIIFD, GLOH, LIOP and LSS. Numéro de notice : A2015-852 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79222
in ISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 62 – 71[article]Measuring the effectiveness of various features for thematic information extraction from very high resolution remote sensing imagery / X. Chen in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)PermalinkSemisupervised transfer component analysis for domain adaptation in remote sensing image classification / Giona Matasci in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)Permalinkvol 25 n° 1 - mars - mai 2015 - Traitement de l'information et prospective (Bulletin de Revue internationale de géomatique) / Françoise GourmelonPermalinkVectorisation automatique des forêts dans les minutes de la carte d’état-major du 19e siècle / Pierre-Alexis Herrault in Revue internationale de géomatique, vol 25 n° 1 (mars - mai 2015)PermalinkIn-flight photogrammetric camera calibration and validation via complementary lidar / A.S. Gneeniss in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkRadiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pléiades-1A stereo images for 3D information extraction / Daniela Poli in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)PermalinkPermalinkExtraction de fragments forestiers et caractérisation de leurs évolutions spatio-temporelles pour évaluer l'effet de l'histoire sur la biodiversité : une approche multi-sources / Pierre-Alexis Herrault (2015)PermalinkHierarchical extraction of urban objects from mobile laser scanning data / Bisheng Yang in ISPRS Journal of photogrammetry and remote sensing, vol 99 (January 2015)PermalinkAutomatic building extraction using a fuzzy active contour model / Mostafa Kabolizade in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)PermalinkPer-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery / Mustafa Neamah Jebur in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)PermalinkApport de l'imagerie satellitaire à haute et très haute résolution pour la recherche d'indices de drainage superficiel : Application aux aires d'alimentation de captage (AAC) d'eau potable / Sébastien Rucquoi in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)PermalinkDetecting cars in UAV images with a catalog-based approach / Thomas Moranduzzo in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)PermalinkGround and building extraction from LiDAR data based on differential morphological profiles and locally fitted surfaces / Domen Mongus in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)PermalinkComparaison de méthodes d'extraction automatique à partir d'images multispectrales / Valerio Baiocchi in Géomatique expert, n° 96 (01/01/2014)PermalinkUsing mobile laser scanning data for automated extraction of road markings / Haiyan Guan in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkAn automated algorithm for extracting road edges from terrestrial mobile LiDAR data / Pankaj Kumar in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)PermalinkSingle tree biomass modelling using airborne laser scanning / Ville Kankare in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)PermalinkPedestrian network extraction from fused aerial imagery (orthoimages) and laser imagery (lidar) / Piyawan Kasemsuppakorn in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 4 (April 2013)PermalinkPermalink