Sar Image Despeckling

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Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (22 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• SAR2SAR: a semi-supervised despeckling algorithm for SAR images
  26 Jun 2020 5 repositories listed
  A study with synthetic speckle noise is presented to compare the performances of the proposed method with other state-of-the-art filters.
• SAR Image Despeckling Using a Convolutional Neural Network
  2 Jun 2017 3 repositories listed
  Synthetic Aperture Radar (SAR) images are often contaminated by a multiplicative noise known as speckle.
• As if by magic: self-supervised training of deep despeckling networks with MERLIN
  25 Oct 2021 2 repositories listed
  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…
• Deep Learning Based Speckle Filtering for Polarimetric SAR Images. Application to Sentinel-1
  28 Aug 2024 1 repository listed
  A wide variety of methods, using either spatially-based approaches or transform-based strategies, have been developed and have shown to provide outstanding results.
• Transformer-based SAR Image Despeckling
  23 Jan 2022 1 repository listed
  Synthetic Aperture Radar (SAR) images are usually degraded by a multiplicative noise known as speckle which makes processing and interpretation of SAR images difficult.
• SAR Image Despeckling Using Continuous Attention Module
  2 Dec 2021 1 repository listed
  Although this architecture extracts features on different scales and has been shown to yield state-of-the-art performance, it still learns representation locally, resulting in missing overall information of…
• Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentation
  1 Feb 2021 1 repository listed
  This paper presents a despeckling method for Sentinel-1 GRD images based on the recently proposed framework "SAR2SAR": a self-supervised training strategy.
• Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks
  4 Jul 2020 1 repository listed
  Information extraction from synthetic aperture radar (SAR) images is heavily impaired by speckle noise, hence despeckling is a crucial preliminary step in scene analysis algorithms.
• SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy
  28 Jun 2020 1 repository listed
  Many different schemes have been proposed for the restoration of intensity SAR images.
• Guided patch-wise nonlocal SAR despeckling
  28 Nov 2018 1 repository listed
  We propose a new method for SAR image despeckling which leverages information drawn from co-registered optical imagery.
• Learning a Dilated Residual Network for SAR Image Despeckling
  9 Sep 2017 1 repository listed
  In this paper, to break the limit of the traditional linear models for synthetic aperture radar (SAR) image despeckling, we propose a novel deep learning approach by learning a non-linear end-to-end mapping between the…