A decomposition model for scatterers change detection in multi-temporal series of SAR images
- Resource Type
- Conference
- Authors
- Lobry, S.; Tupin, F.; Denis, L.
- Source
- 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International. :3362-3365 Jul, 2016
- Subject
- General Topics for Engineers
Signal Processing and Analysis
Synthetic aperture radar
Radiometry
Optimization
Estimation
Time series analysis
Speckle
Detection algorithms
Multi-Temporal Synthetic Aperture Radar (SAR)
Change detection
Image decomposition
TV
L0
- Language
- ISSN
- 2153-7003
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.