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- Centre National de la Recherche ScientifiqueFR83 papers
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8 papers · 1 filter
Logarithmic Mathematical Morphology: Theory and applications
Guillaume Noyel
In Mathematical Morphology for grey-level functions, an image is analysed by another image named the structuring function. This structuring function is translated over the image do…
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…
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…