Search Results for author: Loïc Denis

Found 11 papers, 4 papers with code

A Deep Learning Approach for SAR Tomographic Imaging of Forested Areas

no code implementations20 Jan 2023 Zoé Berenger, Loïc Denis, Florence Tupin, Laurent Ferro-Famil, Yue Huang

Synthetic aperture radar tomographic imaging reconstructs the three-dimensional reflectivity of a scene from a set of coherent acquisitions performed in an interferometric configuration.

Multi-temporal speckle reduction with self-supervised deep neural networks

no code implementations22 Jul 2022 Inès Meraoumia, Emanuele Dalsasso, Loïc Denis, Rémy Abergel, Florence Tupin

Speckle filtering is generally a prerequisite to the analysis of synthetic aperture radar (SAR) images.

Time Series

Fast strategies for multi-temporal speckle reduction of Sentinel-1 GRD images

no code implementations22 Jul 2022 Inès Meraoumia, Emanuele Dalsasso, Loïc Denis, Florence Tupin

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.

Time Series

As if by magic: self-supervised training of deep despeckling networks with MERLIN

1 code implementation25 Oct 2021 Emanuele Dalsasso, Loïc Denis, Florence Tupin

We introduce a self-supervised strategy based on the separation of the real and imaginary parts of single-look complex SAR images, called MERLIN (coMplex sElf-supeRvised despeckLINg), and show that it offers a straightforward way to train all kinds of deep despeckling networks.

Image Denoising Image Restoration +1

Image Restoration for Remote Sensing: Overview and Toolbox

no code implementations1 Jul 2021 Benhood Rasti, Yi Chang, Emanuele Dalsasso, Loïc Denis, Pedram Ghamisi

Additionally, this review paper accompanies a toolbox to provide a platform to encourage interested students and researchers in the field to further explore the restoration techniques and fast-forward the community.

Image Restoration

Urban Surface Reconstruction in SAR Tomography by Graph-Cuts

no code implementations12 Mar 2021 Clément Rambour, Loïc Denis, Florence Tupin, Hélène Oriot, Yue Huang, Laurent Ferro-Famil

This segmentation process can be included within the 3-D reconstruction framework in order to improve the recovery of urban surfaces.

Surface Reconstruction

Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning

no code implementations1 Feb 2021 Emanuele Dalsasso, Inès Meraoumia, Loïc Denis, Florence Tupin

The proposed method combines this multi-temporal average and the image at a given date in the form of a ratio image and uses a state-of-the-art neural network to remove the speckle in this ratio image.

Denoising Time Series

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

1 code implementation1 Feb 2021 Nicolas Gasnier, Emanuele Dalsasso, Loïc Denis, Florence Tupin

This paper presents a despeckling method for Sentinel-1 GRD images based on the recently proposed framework "SAR2SAR": a self-supervised training strategy.

Image Denoising Image Restoration +1

SAR2SAR: a semi-supervised despeckling algorithm for SAR images

4 code implementations26 Jun 2020 Emanuele Dalsasso, Loïc Denis, Florence Tupin

A study with synthetic speckle noise is presented to compare the performances of the proposed method with other state-of-the-art filters.

Image Denoising Image Restoration +2

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