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.
I have recently been notified that my paper about TV+L0 decomposition on multi-temporal series of SAR images is accepted to MultiTemp2015.
SAR signals are different from classical (such as optic) ones because it contains speckle and strong scatterers. This implies that we can not obtain good results with traditional classical image processing techniques on SAR images. In this paper we introduce a regularization that suits multi-temporal series of SAR images combining total variation (TV) and a pseudo-norm L0 regularization.
This model is then optimized using a graphcut technique allowing us to find the global optimum. An application of this result for change detection is presented.
You can download the paper in the Publication section!