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A list of resources to get you started with Deep Learning in Synthetic Aperture Radar(SAR) images

Contents:

1. Introduction
2. Research Papers on Deep Learning based SAR Despeckling
3. Dataset sources
4. Data Processing Applications

Introduction

• Alaska Satellite Facility: What is SAR?

• NASA ARSET: Basics of Synthetic Aperture Radar (SAR), Session 1/4

• NASA ARSET: Basics of Synthetic Aperture Radar (SAR), Session 2/4

Papers

• Deep Learning in SAR Despeckling: Trends and Perspectives [Paper]

• A SURE-Based Unsupervised Deep Learning Method for SAR Despeckling [Paper]

• ID-CNN: SAR Image Despeckling Using a Convolutional Neural Network [Paper] [Code]

• SAR-CNN: SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy [Paper] [Code]

• SAR2SAR: a semi-supervised despeckling algorithm for SAR images [Paper] [Code]

• Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks [ Paper] [Code]

• A Practical Approach for SAR Image Despeckling Using Deep Learning [Paper]

• deSpeckNet: Generalizing Deep Learning Based SAR Image Despeckling [Paper] [Code]

• SAR-CNN (G. Chierchia et al): SAR image despeckling through convolutional neural networks Paper [Code]

• Reference-Free Despeckling of Synthetic-Aperture Radar Images Using a Deep Convolutional Network [Paper] [Code]

Dataset Sources

• Alaska Satellite Facility (ASF)
• Sentinel-1 Copernicus
• TerraSar-X
• RADARSAT

Data Processing Applications

• QGIS

• ArcGIS

• SNAP