Paper accepted at JSTARS

My paper on Multi-temporal SAR image decomposition into strong scatterers, background, and speckle have been accepted at JSTARS.

It will feature a multitemporal decomposition model, that is able to take into account the scatterers that are present in SAR urban images. The model allows for the use of the L0 pseudo-norm for the detection of the scatterers and a prior using the Total Variation (TV) on the image. The optimum solution can be found exactly thanks to Graph-cut optimization. We also show two applications of the model: one for change detection, the other for regularization.

A draft of this paper will be soon available in the publications section.

EUSAR 2016

Last week, I went to EUSAR 2016 in Hamburg to present a method for the classification of water in SWOT images.

This method tries to take into account the variations of the class parameters due to the antenna pattern that cannot be correctly compensated due to the absence of signal in one of the classes. Therefore, we needed to develop a binary classification method, where the parameters are not constant.

You can find the slides here and the article here.