NORCAMA: Change analysis in SAR time series by likelihood ratio change matrix clustering

Abstract :

This paper presents a likelihood ratio test based method of change detection and classification for synthetic aperture radar (SAR) time series, namely NORmalized Cut on chAnge criterion MAtrix (NORCAMA). This method involves three steps: 1) multi-temporal pre-denoising step over the whole image series to reduce the effect of the speckle noise; 2) likelihood ratio test based change criteria between two images using both the original noisy images and the denoised images; 3) change classification by a normalized cut based clustering-and-recognizing method on change criterion matrix (CCM). The experiments on both synthetic and real SAR image series show the effective performance of the proposed framework.

Type de document :
Article dans une revue
ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, 2015, 101, pp.247-261
Liste complète des métadonnées


https://hal-imt.archives-ouvertes.fr/hal-01185740
Contributeur : Admin Télécom Paristech <>
Soumis le : vendredi 21 août 2015 - 13:45:29
Dernière modification le : samedi 18 février 2017 - 01:17:34
Document(s) archivé(s) le : mercredi 26 avril 2017 - 10:18:15

Fichier

article-2015-15643-2.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01185740, version 1

Citation

Xin Su, Charles-Alban Deledalle, Florence Tupin, Hong Sun. NORCAMA: Change analysis in SAR time series by likelihood ratio change matrix clustering. ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, 2015, 101, pp.247-261. <hal-01185740>

Partager

Métriques

Consultations de
la notice

179

Téléchargements du document

169