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

Satellite cloud removal with Deep Image Prior.

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.

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).

DSen2_CR神经网络的pytorch版本

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