SAR Image Despeckling by Deep Neural Networks: from a pre-trained model
to an end-to-end training strategy

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SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy

28 June 2020

Emanuele Dalsasso

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Papers citing "SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy"

6 / 6 papers shown

Title
Deep Learning Based Speckle Filtering for Polarimetric SAR Images. Application to Sentinel-1 Alejandro Mestre-Quereda J. Lopez-Sanchez 51 1 0 28 Aug 2024
Plug-and-Play image restoration with Stochastic deNOising REgularization Marien Renaud Jean Prost Arthur Leclaire Nicolas Papadakis DiffM 156 8 0 01 Feb 2024
As if by magic: self-supervised training of deep despeckling networks with MERLIN Emanuele Dalsasso L. Denis F. Tupin 66 68 0 25 Oct 2021
A speckle filter for Sentinel-1 SAR Ground Range Detected data based on Residual Convolutional Neural Networks A. Sebastianelli M. P. D. Rosso Silvia Liberata Ullo Paolo Gamba 44 15 0 19 Apr 2021
Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning Emanuele Dalsasso Inès Meraoumia L. Denis F. Tupin 49 4 0 01 Feb 2021
Deep Learning Methods For Synthetic Aperture Radar Image Despeckling: An Overview Of Trends And Perspectives Giulia Fracastoro E. Magli Giovanni Poggi Giuseppe Scarpa D. Valsesia L. Verdoliva 59 66 0 10 Dec 2020