  This paper presents a despeckling method for Sentinel-1 GRD images based on
the recently proposed framework "SAR2SAR": a self-supervised training strategy.
Training the deep neural network on collections of Sentinel 1 GRD images leads
to a despeckling algorithm that is robust to space-variant spatial correlations
of speckle. Despeckled images improve the detection of structures like narrow
rivers. We apply a detector based on exogenous information and a linear
features detector and show that rivers are better segmented when the processing
chain is applied to images pre-processed by our despeckling neural network.
