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Cloud Removal

The majority of all optical observations collected via spaceborne satellites are affected by haze or clouds. Consequently, persistent cloud coverage affects the remote sensing practitioner's capabilities of a continuous and seamless monitoring of our planet. Cloud removal is the task of reconstructing cloud-covered information while preserving originally cloud-free details.

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Papers

Showing 110 of 56 papers

TitleStatusHype
Bridging Remote Sensors with Multisensor Geospatial Foundation ModelsCode2
Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing ImageryCode2
Effective Cloud Removal for Remote Sensing Images by an Improved Mean-Reverting Denoising Model with Elucidated Design SpaceCode2
Cloud Removal for Remote Sensing Imagery via Spatial Attention Generative Adversarial NetworkCode1
Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusionCode1
AllClear: A Comprehensive Dataset and Benchmark for Cloud Removal in Satellite ImageryCode1
Cloud Removal in Satellite Images Using Spatiotemporal Generative NetworksCode1
Cloud removal in remote sensing images using generative adversarial networks and SAR-to-optical image translationCode1
Attentive Contextual Attention for Cloud RemovalCode1
DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite ImagesCode1
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