Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks
-
Updated
Mar 24, 2023 - Jupyter Notebook
Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks
SAR2SAR: a self-supervised despeckling algorithm for SAR images - Notebook implementation usable on Google Colaboratory
[IEEE JSTARS] Official PyTorch Implementation of "SAR Image Despeckling Using Continuous Attention Module"
Shared Encoder (SE) based Denoising of Optical Coherence Tomography Images
SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy - Notebook implementation usable on Google Colaboratory
Multi-temporal De-speckling for SAR Backscatter Imagery
Phase asymmetry ultrasound despeckling with fractional anisotropic diffusion and total variation
Self-supervised learning based anomaly detection in synthetic aperture radar imaging
SAR2SAR: a self-supervised despeckling algorithm for SAR images
A FIS designed to despeckle SAR images
Denoising by Quantum Interactive Patches
De-QuIP-Despeckling (Despeckling by Quantum Interactive Patches)
[TAI 2023] Blind Image Despeckling Using Multi-Scale Attention-Guided Neural Network
Speckle2Speckle based despeckling filter for TerraSAR-X Spotlight mode, trained on Colima
SAR2SAR: a self-supervised despeckling algorithm for SAR images
Development of a MATLAB-based Toolbox (Graphical User Interfaces) for Elastogram Image and RF Ultrasound Signal Processing
Add a description, image, and links to the despeckling topic page so that developers can more easily learn about it.
To associate your repository with the despeckling topic, visit your repo's landing page and select "manage topics."