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Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentation

2021-02-01 08:24:25
Nicolas Gasnier, Emanuele Dalsasso, Loïc Denis, Florence Tupin
arXiv_CV
               
Abstract

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.

Abstract (translated)

URL

https://arxiv.org/abs/2102.00692

PDF

https://arxiv.org/pdf/2102.00692.pdf

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