Multivariate Change Detection on High Resolution Monovariate SAR Image Using Linear Time-Frequency Analysis

Ammar Mian (1) , Jean-Philippe Ovarlez (1) , Guillaume Ginolhac (2) , A Atto (2)

1 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay (COmUE)
2 LISTIC - Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance

In this paper, we propose a novel methodology for Change Detection between two monovariate complex SAR images. Linear Time-Frequency tools are used in order to recover a spectral and angular diversity of the scatterers present in the scene. This diversity is used in bi-date change detection framework to develop a detector, whose performances are better than the classic detector on monovariate SAR images.

Domaines: Traitement du signal et de l'image [eess.SP]

Ammar Mian, Jean-Philippe Ovarlez, Guillaume Ginolhac, A Atto. Multivariate Change Detection on High Resolution Monovariate SAR Image Using Linear Time-Frequency Analysis. 25th European Signal Processing Conference (EUSIPCO 2017), Aug 2017, Kos Island, Greece. ⟨10.23919/EUSIPCO.2017.8081548⟩. ⟨hal-01617069⟩