deploy remote sensing imagery cloud removal model online

Cloud Removal for High-resolution Remote Sensing Imagery based on Generative Adversarial Networks.

Removing cloud cover in Sentinel-2 satellite images using only optical data and a novel augmented training approach using conditional GANs.

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.

GLF-CR: SAR-Enhanced Cloud Removal with Global-Local Fusion

The software called Fmask (Function of mask) is used for automated clouds, cloud shadows, and snow masking for Landsats 4-8 and Sentinel 2 images.

Sentinel Hub Cloud Detector for Sentinel-2 images in Python

Multimodal and Multiresolution Data Fusion for High-Resolution Cloud Removal: A Novel Baseline and Benchmark

[TGRS 2024] DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite Images

Cloud mask with Landsat 8 and Sentinel 2.