Détail de l'auteur
Auteur Ahmad Izadipour |
Documents disponibles écrits par cet auteur (1)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
![Tris disponibles](./images/orderby_az.gif)
A feature selection approach for segmentation of very high-resolution satellite images / Ahmad Izadipour in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 3 (March 2016)
![]()
[article]
Titre : A feature selection approach for segmentation of very high-resolution satellite images Type de document : Article/Communication Auteurs : Ahmad Izadipour, Auteur ; Behzad Akbari, Auteur ; Barat Mojaradi, Auteur Année de publication : 2016 Article en page(s) : pp 213 - 222 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image Geoeye
[Termes IGN] image Quickbird
[Termes IGN] résolution globale (imagerie)
[Termes IGN] segmentation d'imageRésumé : (auteur) Most of the feature selection (FS) methods in the literature determine features that are appropriate only for a given dataset. In contrast, in this paper a FS method that is not dependent to a specific dataset is proposed. In this regard, the effective feature types based on reasonable facts are predefined and appropriate candidate features for each feature type are selected. In proposed method, the features selected from a single labeled image can be used in segmentation of images captured by different satellites with similar spatial resolution. The selected feature types contain spatial and spectral features. The selected features are applied for segmentation of the images captured by QuickBird and GeoEye satellites and obtained results of proposed method are compared with well-known FS methods. Using different evaluation measures, our comparison shows the efficiency of the proposed method in providing better segmentation compared to other FS methods that are presented in this paper. Numéro de notice : A2016-178 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.3.213 En ligne : https://doi.org/10.14358/PERS.82.3.213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80519
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 3 (March 2016) . - pp 213 - 222[article]