Study of segmentation-classification interactions within a multi-paradigm framework for remote sensing image analysis

Study of segmentation-classification interactions within a multi-paradigm framework for remote sensing image analysis

Andrés Troya-Galvis Pierre Gançarski Laure Berti-Équille 

ICube, Université de Strasbourg 300 bd Sébastien Brant - CS 10413 - F-67412 Illkirch Cedex, France

Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar

Espace-Dev UMR 228, IRD - Université de Montpellier, 500 Rue J.F. Breton, 34090 Montpellier, France

Corresponding Author Email: 
troyagalvis@unistra.fr; gancarski@unistra.fr; lberti@qf .org.qa; Laure.Berti@ird.fr
Page: 
133-152
|
DOI: 
https://doi.org/10.3166/RIA.31.133-152
Received: 
|
Accepted: 
|
Published: 
30 April 2017
| Citation
Abstract: 

Segmentation and classification tasks are closely related in the remote sensing image analysis domain. Collaborative approaches allow interactions between segmentation and classification techniques in order to mutually improve both results. In this article we present a generic collaborative framework for segmentation and classification of remote sensing images, and we make an exploratory study comparing a large number of collaboration strategies in order to better understand the interactions between these paradigms.

Keywords: 

segmentation, classification, remote sensing image analysis

1. Introduction
2. Le cadre collaboratif CoSC
3. Implémentation du processus CoSC
4. Étude du comportement de CoSC en fonction de ses paramètres
5. Discussion
6. Conclusion
Remerciements

Ces travaux de recherche ont été financés par l’Agence Nationale de la Recherche dans le cadre du projet COCLICO (ANR-12-MONU-0001).

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