Cloud Removal for High-resolution Remote Sensing Imagery based on Generative Adversarial Networks.
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Updated
Jul 14, 2023 - Python
Cloud Removal for High-resolution Remote Sensing Imagery based on Generative Adversarial Networks.
DSen2-CR: A network for removing clouds from Sentinel-2 images. This repo contains the model code, written in Python/Keras, as well as links to pre-trained checkpoints and the SEN12MS-CR dataset.
Code for paper: Memory Augment is All Your Need for image restoration(cloud,rain,shadow removal, low-light image enhancement, image deblur)即插即用提点的记忆模块
Q. Zhang, Q. Yuan, J. Li, Z. Li, H. Shen, and L. Zhang, "Thick Cloud and Cloud Shadow Removal in Multitemporal Images using Progressively Spatio-Temporal Patch Group Learning", ISPRS Journal, 2020.
Satellite cloud removal with Deep Image Prior.
CloudGAN: Detecting and removing clouds from satellite RGB-images
Official PyTorch implementation of "PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-Performance Cloud Removal from Multi-temporal Satellite Imagery" (ECAI 2023).
This is the official code of the paper "Cloud removal using SAR and optical images via attention mechanism-based GAN"
Seamless Flood Mapping Using Harmonized Landsat and Sentinel-2 Data
Developed an AI System based on Generative Adversarial Networks (GANs) to predict and remove the Clouds and Fog from an Image captured from Satellite. Gets input of a Satellite Image with Clouds and outputs a predicted landscape without clouds. Demo prototype for my internship at ISRO Hyderabad campus National Remote Sensing Centre. Actual proje…
Missing Information Reconstruction Integrating Isophote Constraint and Color- Structure Control for Remote Sensing Data
A curvature-driven cloud removal method for remote sensing images
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