159 citations · 527 across the 9 of their papers we have counts for
10 papers
Just Project! Multi-Channel Despeckling, the Easy Way
Loïc Denis, Emanuele Dalsasso, Florence Tupin
Reducing speckle fluctuations in multi-channel SAR images is essential in many applications of SAR imaging such as polarimetric classification or interferometric height estimation.…
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…
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…
Image Restoration for Remote Sensing: Overview and Toolbox
Benhood Rasti, Yi Chang, Emanuele Dalsasso +2
Remote sensing provides valuable information about objects or areas from a distance in either active (e.g., RADAR and LiDAR) or passive (e.g., multispectral and hyperspectral) mode…
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…