@inproceedings{c8af57111a9449c297a05cb63b6d170b,
title = "A decomposition model for scatterers change detection in multi-temporal series of SAR images",
abstract = "This paper presents a method for strong scatterers change detection in synthetic aperture radar (SAR) images based on a decomposition for multi-temporal series. The formulated decomposition 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 occurred. An exact optimization method of the model is presented and applied to a TerraSAR-X time series.",
keywords = "Change detection, Image decomposition, L0, Multi-Temporal Synthetic Aperture Radar (SAR), TV",
author = "S. Lobry and F. Tupin and L. Denis",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7729869",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3362--3365",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
}