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07/15/2023
Multitemporal SAR images change detection and visualization using RABASAR and simplified GLR
Understanding the state of changed areas requires that precise informati...
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01/20/2023
A Deep Learning Approach for SAR Tomographic Imaging of Forested Areas
Synthetic aperture radar tomographic imaging reconstructs the three-dime...
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07/22/2022
Fast strategies for multi-temporal speckle reduction of Sentinel-1 GRD images
Reducing speckle and limiting the variations of the physical parameters ...
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07/22/2022
Multi-temporal speckle reduction with self-supervised deep neural networks
Speckle filtering is generally a prerequisite to the analysis of synthet...
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12/10/2021
unrolling palm for sparse semi-blind source separation
Sparse Blind Source Separation (BSS) has become a well established tool ...
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10/25/2021
As if by magic: self-supervised training of deep despeckling networks with MERLIN
Speckle fluctuations seriously limit the interpretability of synthetic a...
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03/30/2021
Multi-View Radar Semantic Segmentation
Understanding the scene around the ego-vehicle is key to assisted and au...
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03/12/2021
Urban Surface Reconstruction in SAR Tomography by Graph-Cuts
SAR (Synthetic Aperture Radar) tomography reconstructs 3-D volumes from ...
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02/01/2021
Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentation
This paper presents a despeckling method for Sentinel-1 GRD images based...
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02/01/2021
Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning
Deep learning approaches show unprecedented results for speckle reductio...
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06/28/2020
SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy
Speckle reduction is a longstanding topic in synthetic aperture radar (S...
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06/26/2020