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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 2130 of 56 papers

TitleStatusHype
Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing ImageryCode2
Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection0
DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite ImagesCode1
Cloud Removal in Remote Sensing Using Sequential-Based Diffusion Models0
U-TILISE: A Sequence-to-sequence Model for Cloud Removal in Optical Satellite Time SeriesCode1
On-board Change Detection for Resource-efficient Earth Observation with LEO Satellites0
UnCRtainTS: Uncertainty Quantification for Cloud Removal in Optical Satellite Time SeriesCode1
PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-performance Cloud Removal from Multi-temporal Satellite ImageryCode1
Multi-Modal and Multi-Resolution Data Fusion for High-Resolution Cloud Removal: A Novel Baseline and BenchmarkCode1
MM811 Project Report: Cloud Detection and Removal in Satellite Images0
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