A Multilayer Markovian Model for Change Detection in Aerial Image Pairs with Large Time Differences

Praveer Singh 1 Zoltan Kato 2 Josiane Zerubia 1
1 AYIN - Models of spatio-temporal structure for high-resolution image processing
CRISAM - Inria Sophia Antipolis - Méditerranée
2 Institute of Informatics
Abstract : In this paper, we propose a Multilayer Markovian model for change detection in registered aerial image pairs with large time differences. A Three Layer Markov Random Field takes into account information from two different sets of features namely the Modified HOG (Histogram of Oriented Gradients) difference and the Gray-Level (GL) Difference. The third layer is the resultant combination of the two layers. Thus we integrate both the texture level as well as the pixel level information to generate the final result. The proposed model uses pairwise interaction retaining the sub-modularity condition for energy. Hence a global energy optimization can be achieved using a standard min-cut/ max flow algorithm ensuring homogeneity in the connected regions.
Type de document :
Communication dans un congrès
International Conference on Pattern Recognition (ICPR'14), Aug 2014, Stockholm, Sweden. 2014
Liste complète des métadonnées

Littérature citée [16 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01016820
Contributeur : Praveer Singh <>
Soumis le : mardi 1 juillet 2014 - 11:12:23
Dernière modification le : jeudi 6 septembre 2018 - 17:10:02
Document(s) archivé(s) le : mercredi 1 octobre 2014 - 12:10:29

Fichier

ICPR14_0633_FI.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01016820, version 1

Collections

INRIA

Citation

Praveer Singh, Zoltan Kato, Josiane Zerubia. A Multilayer Markovian Model for Change Detection in Aerial Image Pairs with Large Time Differences. International Conference on Pattern Recognition (ICPR'14), Aug 2014, Stockholm, Sweden. 2014. 〈hal-01016820〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

425

Téléchargements de fichiers

334

Contact


archive-ouverte@inria.fr