A list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks.
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Updated
Mar 29, 2024
A list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks.
Algorithms and utilities for Synthetic Aperture Radar (SAR) sensors
A basic Python library to demonstrate reading, writing, display, and simple processing of complex SAR data using the NGA SICD standard.
Xarray backend to Copernicus Sentinel-1 satellite data products
A basic MATLAB library to demonstrate reading, writing, display, and simple processing of complex SAR data using the NGA SICD standard.
Flood Python Toolbox
Maritime vessel detection from remote sensing SAR data, based on the architectures of the Faster-RCNN and YOLOv5 networks.
Vessel Detection in Synthetic Aperture Radar(SAR) Images
Hephaestus: A large scale multitask dataset towards InSAR understanding
We’ve built a plug’n play Operation System (based on Debian Linux) with all the freely and openly available SAR processing software. No knowledge of installation steps needed, just download and get started with SAR data processing. SARbian is free for use in research, education or operational work.
Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks
Python Based Simulation and Analysis tool for Synthetic Aperture Radar
Spekle reduction of SAR images in matlab using different custom-made filters: -Mean filter. -Frost filter. -Modified frost filter(added thresholds). -Lee filter(Using Masks, ENL ect). Note these fitlers are developed without the use of loops to make them faster.
Machine Learning for Synthetic Aperture Radar Autofocus
Land Cover Change Detection using Satellite Image Segmentation.
NDSAR speckle filtering for multidimensional and single-channel SAR images
SAR2SAR: a self-supervised despeckling algorithm for SAR images - Notebook implementation usable on Google Colaboratory
This repository contains a pipeline blending Python and R features, first to: download, preprocess, and compute Sentinel-1 SAR vegetation indices (all in Python); following for image sampling in R.
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