Descripteur
Termes IGN > mathématiques > statistique mathématique > analyse de données > classification > classification floue
classification floue |
Documents disponibles dans cette catégorie (87)
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
Titre : Automatische Extraktion von Bäumen aus Fernerkundungsdaten Titre original : [Extraction automatique des arbres à partir des données de télédétection] Type de document : Thèse/HDR Auteurs : B.M. Straub, Auteur Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2003 Collection : DGK - C Sous-collection : Dissertationen num. 572 Importance : 97 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-7696-5011-2 Note générale : Bibliographie Langues : Allemand (ger) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre (flore)
[Termes IGN] classification floue
[Termes IGN] extraction automatique
[Termes IGN] objet géographique zonal
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation d'imageIndex. décimale : 35.20 Traitement d'image Résumé : (Auteur) A new approach for automatic extraction of trees from remote sensing data - aerial imagery and surface models - is introduced in this thesis. A detailed description of the most important considerations, leading to the development of the approach, is given: for the model of an individual tree, which is the base of the approach and for the strategy for low-level feature extraction and generation of hypotheses. In addition to that, the extraction of individual trees is discussed in relation to other topographic objects. The aim of this discussion is showing possibilities for the integration of the approach for trees into a system for automatic interpretation of remote sensing data. Here, extraction should be understood as the cognitive recognition of objects and their identification and reconstruction. The process of object extraction from images and/or surface models generally depends on an object model as well as a strategy for extraction of image features, their combination, and their relation to the model. A generic geometric model of a tree is used which basically consists of a function describing the tree top. Based on this model features are identified, which are used to recognise single trees from the image data. The basic idea for this strategy consists of two steps. At first, the often very complex fine structures are removed from the surface model by using various scale levels in linear scale space. As a result of scale-space transformation the tree top can be identified in the surface model based on the coarse structure. Here, the main problem is, that on the one hand the diameter of a single tree continuously varies in reality, but also strongly influences the choice of filter parameters. To overcome this difficulty, the image data was examined at different scale levels of linear scale-space. The extraction of the trees is performed using an algorithm: Firstly, segmentation of each scale-level with the watershed transformation is carried out. The resulting segments, which are potential candidates for tree tops, are evaluated with the help of fuzzy functions and based on the resulting membership values hypotheses are generated. The last step is the reconstruction of the crown's outline using a snake-algorithm. The procedure, developed for the extraction of trees from images and surface models in the context of this thesis, is applied in various small test areas. The positive as well as the negative results of these projects are presented, and the problems are discussed based on subsets of the test areas. An evaluation of the approach, and proposals for further development and research are given at the end of the thesis. Numéro de notice : 13202 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère DOI : sans En ligne : https://dgk.badw.de/fileadmin/user_upload/Files/DGK/docs/c-572.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=54912 Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 13202-01 35.20 Livre Centre de documentation Télédétection Disponible 13202-02 35.20 Livre Centre de documentation Télédétection Disponible Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions / Robert Gilmore Pontius in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 10 (October 2002)
[article]
Titre : Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions Type de document : Article/Communication Auteurs : Robert Gilmore Pontius, Auteur Année de publication : 2002 Article en page(s) : pp 1041 - 1049 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] analyse de données
[Termes IGN] classification floue
[Termes IGN] Costa Rica
[Termes IGN] déboisement
[Termes IGN] forêt
[Termes IGN] modèle de simulationRésumé : (Auteur) New generalized statistical methods to measure agreement between two maps at multiple-resolutions, where each cell in each map has a multinomial distribution among any number of categories, are presented. This methodology quantifies agreement between any two categorical maps, where either map uses fuzzy or crisp classification. The method measures the agreement at various resolutions by aggregating neighboring cells into an increasingly coarse grid. At each resolution, the method partitions the overall agreement into correct due to chance, correct due to quantity, correct due to location, error due to location, and error due to quantity. In addition, the method computes six statistics that are useful to interpret the differences between maps, and shows how these statistics change with resolution. This technique is particularly useful for characterizing land-cover change and for validating landcover change models. For illustration, this paper applies these theoretical concepts to the validation of a land-use change model for Costa Rica. Numéro de notice : A2002-234 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : sans En ligne : https://www2.clarku.edu/~rpontius/pontius_2002_pers.pdf Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22148
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 10 (October 2002) . - pp 1041 - 1049[article]A comparison of fuzzy vs. augmented-ISODATA classification algorithms for cloud-shadow discrimination from Landsat images / A.M. Melesse in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 9 (September 2002)
[article]
Titre : A comparison of fuzzy vs. augmented-ISODATA classification algorithms for cloud-shadow discrimination from Landsat images Type de document : Article/Communication Auteurs : A.M. Melesse, Auteur ; J.D. Jordan, Auteur Année de publication : 2002 Article en page(s) : pp 905 - 911 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] bande visible
[Termes IGN] classification dirigée
[Termes IGN] classification floue
[Termes IGN] classification ISODATA
[Termes IGN] image Landsat-TM
[Termes IGN] nuage
[Termes IGN] ombreRésumé : (Auteur) Satellite images are the most important source of landcover data over a large range of temporal and spatial scales. However, the complete realization of satellite imagery as a source of landcover information is limited by the presence of contaminants such as cloud and associated shadows in the image. These contaminants are not adequately handled with conventional image classification techniques such as the unsupervised maximumlikelihood technique. This study comprises a comparison of two classification algorithms, the fuzzy technique and an augmented form of the Iterative SelfOrganizing Data Analysis (ISODATA) technique, which were used to discriminate lowaltitude clouds and their shadows on a Landsat Thematic Mapper (TM) image of the Econlockhatchee River basin (Econ), in central Florida. Preliminary conventional unsupervised maxim umlikelihood classification of the image resulted in clouds being mixed with builtups and shadows being mixed with water bodies. Regions containing these two kinds of mixed categories were first masked, then fuzzy and augmented ISODATA classifications were performed on them. The ISODATA classification algorithm was run on the TM visible/shortwave bands and augmented with scatter diagrams of surface temperature versus several vegetation indices; the fuzzy algorithm was run on TM bands 1 through 5 and band 7. An accuracy assessment of the techniques was carried out using 40 randomly selected points within the image. Results of the classifications showed that both algorithms successfully discriminated clouds from other bright features, and shadows from other dark features, with an overall accuracy of greater than 80 percent. Numéro de notice : A2002-182 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/september/2002_sep_905 [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22097
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 9 (September 2002) . - pp 905 - 911[article]Fuzzy rule-based classification of remotely sensed imagery / A. Bardossy in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)
[article]
Titre : Fuzzy rule-based classification of remotely sensed imagery Type de document : Article/Communication Auteurs : A. Bardossy, Auteur ; L. Samaniego, Auteur Année de publication : 2002 Article en page(s) : pp 362 - 374 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes IGN] classification dirigée
[Termes IGN] classification floue
[Termes IGN] image Landsat
[Termes IGN] occupation du sol
[Termes IGN] simulationRésumé : (Auteur) The purpose of this paper is to investigate the applicability of fuzzy rule-based modeling to classify a LANDSAT TM scene from 1984 of an area located in the south of Germany. Both a land cover map with four different categories and an image depicting the degree of ambiguity of the classification for each pixel is the expected output. The fuzzy classification algorithm will use a rule system derived from a training set using simulated annealing as an optimization algorithm. The results are then validated and compared with a common classification method in order to judge the effectiveness of the proposed technique. It will also be shown that the proposed method with only nine rules for four different land cover classes performs slightly better than the maximum likelihood classifier (MLC). For error assessment, the traditional error matrix and fuzzy operators have been used. Numéro de notice : A2002-096 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.992798 En ligne : https://doi.org/10.1109/36.992798 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22011
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 2 (February 2002) . - pp 362 - 374[article]Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 065-02021 RAB Revue Centre de documentation En réserve L003 Disponible 065-02022 RAB Revue Centre de documentation En réserve L003 Disponible Detection of urban structures in SAR images by robust fuzzy clustering algorithms: the example of street tracking / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 39 n° 10 (October 2001)
[article]
Titre : Detection of urban structures in SAR images by robust fuzzy clustering algorithms: the example of street tracking Type de document : Article/Communication Auteurs : F. Dell'acqua, Auteur ; Paolo Gamba, Auteur Année de publication : 2001 Article en page(s) : pp 2287 - 2297 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse de groupement
[Termes IGN] chemin le plus court, algorithme du
[Termes IGN] classification floue
[Termes IGN] extraction automatique
[Termes IGN] image aérienne
[Termes IGN] image radar moirée
[Termes IGN] logique floue
[Termes IGN] milieu urbain
[Termes IGN] réseau routier
[Termes IGN] route
[Termes IGN] transformation de HoughRésumé : (Auteur) In this work, we present a fuzzy approach to the analysis of airborne synthetic aperture radar (SAR) images of urban environments. In particular, we want to show how to implement structure extraction algorithms based on fuzzy clustering unsupervised approaches. To this aim, the idea is to segment first the sensed data and recognize very basic urban classes (vegetation, roads, and built areas). Then, from these classes, we extract structures and infrastructures of interest. The initial clustering step is obtained by means of fuzzy logic concepts and the successive analyses are able to exploit the corresponding fuzzy partition. As a possible complete procedure for urban SAR images, in this paper, we focus on the street tracking and extraction problem. Three road extraction algorithms available in literature (namely, the connectivity weighted Hough transform (CWHT), the rotation Hough transform, and the shortest path extraction) have been modified to be consistent with the previously computed fuzzy clustering results. Their different capabilities are applied for the characterization of streets with different width and shape. The whole approach is validated by the analysis of AIRSAR images of Los Angeles, CA. Numéro de notice : A2001-095 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.957292 En ligne : https://doi.org/10.1109/36.957292 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21795
in IEEE Transactions on geoscience and remote sensing > vol 39 n° 10 (October 2001) . - pp 2287 - 2297[article]Réservation
Réserver ce documentExemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 065-01101 RAB Revue Centre de documentation En réserve L003 Disponible 065-01102 RAB Revue Centre de documentation En réserve L003 Disponible Cartogenèse numérique des types de sols et de leurs incertitudes par la combinaison de corrélations sur les facteurs environnementaux et des géostatistiques : application aux sols des environs de La Rochelle / F. Carre in Photo interprétation, vol 38 n° 3-4 (Septembre 2000)PermalinkAdvanced polarimetric SAR data classification for cartographic information extraction / Manfred F. Buchroithner (31/05/1999)PermalinkAdvances in remote sensing and GIS analysis, [selected papers from a meeting held at the University of Southampton, July 25, 1996] / P.M. Atkinson (1999)PermalinkRSS 99 Earth observation / P. Pan (1999)PermalinkCartographie semi-automatique de l'évolution de l'occupation des sols par télédétection / Hervé Le Men (1996)PermalinkPermalinkCloud classification from satellite data using a fuzzy sets algorithm: a polar example / J.R. Key in International Journal of Remote Sensing IJRS, vol 10 n° 12 (December 1989)Permalink