15 citations · 16 across the 2 of their papers we have counts for
8 papers
Urban Surface Reconstruction in SAR Tomography by Graph-Cuts
Clément Rambour, Loïc Denis, Florence Tupin +3
SAR (Synthetic Aperture Radar) tomography reconstructs 3-D volumes from stacks of SAR images. High-resolution satellites such as TerraSAR-X provide images that can be combined to p…
Multi-View Radar Semantic Segmentation
Arthur Ouaknine, Alasdair Newson, Patrick Pérez +2
Understanding the scene around the ego-vehicle is key to assisted and autonomous driving. Nowadays, this is mostly conducted using cameras and laser scanners, despite their reduced…
Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentation
Nicolas Gasnier, Emanuele Dalsasso, Loïc Denis +1
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…
Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning
Emanuele Dalsasso, Inès Meraoumia, Loïc Denis +1
Deep learning approaches show unprecedented results for speckle reduction in SAR amplitude images. The wide availability of multi-temporal stacks of SAR images can improve even fur…
A review of deep-learning techniques for SAR image restoration
Loïc Denis, Emanuele Dalsasso, Florence Tupin
The speckle phenomenon remains a major hurdle for the analysis of SAR images. The development of speckle reduction methods closely follows methodological progress in the field of i…
SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy
Emanuele Dalsasso, Xiangli Yang, Loïc Denis +2
Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) images. Many different schemes have been proposed for the restoration of intensity SAR images. Among the…