SELF-SUPERVISED LEARNING OF MULTI-MODAL COOPERATION FOR SAR DESPECKLING
Résumé
Synthetic aperture radar (SAR) is a widely used modality for Earth observation, as they provide weather-independent imaging capabilities. However, interpretation of SAR images is difficult due to the speckle phenomenon: fluctuations appear in the image, which are stronger in areas with high radar reflectivity. As a result, many speckle reduction methods have been developed, with deep learning approaches standing out as particularly effective. Our article presents here a deep learning approach with two novel features: the use of an optical image to improve the restoration of a SAR image, while using a self-supervised neural network training
Domaines
Informatique [cs]| Origine | Fichiers produits par l'(les) auteur(s) |
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