Abstract : This paper presents a method for strong scatterers change de-
tection in synthetic aperture radar (SAR) images based on a
decomposition for multi-temporal series. The formulated de-
composition model jointly estimates the background of the
series and the scatterers. The decomposition model retrieves
possible changes in scatterers and the date at which they oc-
curred. An exact optimization method of the model is pre-
sented and applied to a TerraSAR-X time series.
Sylvain Lobry, Florence Tupin, L. Denis. A decomposition model for scatterers change detection in multi-temporal series of SAR images. IGARSS, Jul 2016, Pékin, China. ⟨hal-02287350⟩