Region-based classification of remote sensing images with the morphological tree of shapes

Gabriele Cavallaro 1 Mauro Dalla Mura 2 Edwin Carlinet 3, 4 Thierry Géraud 3 Nicola Falco 1 Jón Benediktsson 1
1 University of Iceland [Reykjavik]
2 GIPSA-SIGMAPHY - SIGMAPHY
GIPSA-DIS - Département Images et Signal
3 LRDE - Laboratoire de Recherche et de Développement de l'EPITA
4 LIGM - Laboratoire d'Informatique Gaspard-Monge
Abstract : Satellite image classification is a key task used in remote sensing for the automatic interpretation of a large amount of information. Today there exist many types of classification algorithms using advanced image processing methods enhancing the classification accuracy rate. One of the best state-of-the-art methods which improves significantly the classification of complex scenes relies on Self-Dual Attribute Profiles (SDAPs). In this approach, the underlying representation of an image is the Tree of Shapes, which encodes the inclusion of connected components of the image. The SDAP computes for each pixel a vector of attributes providing a local multi-scale representation of the information and hence leading to a fine description of the local structures of the image. Instead of performing a pixel-wise classification on features extracted from the Tree of Shapes, it is proposed to directly classify its nodes. Extending a specific interactive segmentation algorithm enables it to deal with the multi-class classification problem. The method does not involve any statistical learning and it is based entirely on morphological information related to the tree. Consequently, a very simple and effective region-based classifier relying on basic attributes is presented.
Keywords : Remote Sensing Classification Mathematical Morphology Tree of Shapes
Type de document :
Communication dans un congrès
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , Jul 2016, Beijing, China. pp.5087 - 5090, 2016, 〈10.1109/IGARSS.2016.7730326〉
Liste complète des métadonnées

Littérature citée [21 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01476244
Contributeur : Thierry Géraud <>
Soumis le : vendredi 24 février 2017 - 16:32:08
Dernière modification le : mardi 10 juillet 2018 - 01:18:46
Document(s) archivé(s) le : jeudi 25 mai 2017 - 13:44:16

Fichier

Manuscript_submitted.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

UPEC-UPEM | GIPSA-SIGMAPHY | LIGM | ENPC | PARISTECH | LIGM_A3SI | UGA | GIPSA | GIPSA-DIS | ESIEE-PARIS

Citation

Gabriele Cavallaro, Mauro Dalla Mura, Edwin Carlinet, Thierry Géraud, Nicola Falco, et al.. Region-based classification of remote sensing images with the morphological tree of shapes. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , Jul 2016, Beijing, China. pp.5087 - 5090, 2016, 〈10.1109/IGARSS.2016.7730326〉. 〈hal-01476244〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

557

Téléchargements de fichiers

24

Contact


archive-ouverte@inria.fr