176 citations · 589 across the 16 of their papers we have counts for
18 papers
Multi-view 3D surface reconstruction from SAR images by inverse rendering
Emile Barbier--Renard, Florence Tupin, Nicolas Trouvé +1
3D reconstruction of a scene from Synthetic Aperture Radar (SAR) images mainly relies on interferometric measurements, which involve strict constraints on the acquisition process.…
Patch-based adaptive temporal filter and residual evaluation
Weiying Zhao, Paul Riot, Charles-Alban Deledalle +3
In coherent imaging systems, speckle is a signal-dependent noise that visually strongly degrades images' appearance. A huge amount of SAR data has been acquired from different sens…
Multitemporal SAR images change detection and visualization using RABASAR and simplified GLR
Weiying Zhao, Charles-Alban Deledalle, Loïc Denis +3
Understanding the state of changed areas requires that precise information be given about the changes. Thus, detecting different kinds of changes is important for land surface moni…
A Deep Learning Approach for SAR Tomographic Imaging of Forested Areas
Zoé Berenger, Loïc Denis, Florence Tupin +2
Synthetic aperture radar tomographic imaging reconstructs the three-dimensional reflectivity of a scene from a set of coherent acquisitions performed in an interferometric configur…
Multi-temporal speckle reduction with self-supervised deep neural networks
Inès Meraoumia, Emanuele Dalsasso, Loïc Denis +2
Speckle filtering is generally a prerequisite to the analysis of synthetic aperture radar (SAR) images. Tremendous progress has been achieved in the domain of single-image despeckl…
Fast strategies for multi-temporal speckle reduction of Sentinel-1 GRD images
Inès Meraoumia, Emanuele Dalsasso, Loïc Denis +1
Reducing speckle and limiting the variations of the physical parameters in Synthetic Aperture Radar (SAR) images is often a key-step to fully exploit the potential of such data. No…
Unrolling PALM for sparse semi-blind source separation
Mohammad Fahes, Christophe Kervazo, Jérôme Bobin +1
Sparse Blind Source Separation (BSS) has become a well established tool for a wide range of applications - for instance, in astrophysics and remote sensing. Classical sparse BSS me…
As if by magic: self-supervised training of deep despeckling networks with MERLIN
Emanuele Dalsasso, Loïc Denis, Florence Tupin
Speckle fluctuations seriously limit the interpretability of synthetic aperture radar (SAR) images. Speckle reduction has thus been the subject of numerous works spanning at least…
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…
SAR2SAR: a semi-supervised despeckling algorithm for SAR images
Emanuele Dalsasso, Loïc Denis, Florence Tupin
Speckle reduction is a key step in many remote sensing applications. By strongly affecting synthetic aperture radar (SAR) images, it makes them difficult to analyse. Due to the dif…
CARRADA Dataset: Camera and Automotive Radar with Range-Angle-Doppler Annotations
A. Ouaknine, A. Newson, J. Rebut +2
High quality perception is essential for autonomous driving (AD) systems. To reach the accuracy and robustness that are required by such systems, several types of sensors must be c…
MuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction?
Charles-Alban Deledalle, Loïc Denis, Sonia Tabti +1
Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric…
Template matching with noisy patches: A contrast-invariant GLR test
Charles-Alban Deledalle, Loïc Denis, Florence Tupin
Matching patches from a noisy image to atoms in a dictionary of patches is a key ingredient to many techniques in image processing and computer vision. By representing with a singl…