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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

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Showing 41–50 of 56 papers

TitleStatusHype
Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection—0
Enhancing Satellite Imagery using Deep Learning for the Sensor To Shooter Timeline—0
Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets—0
Haar Nuclear Norms with Applications to Remote Sensing Imagery Restoration—0
MIMRS: A Survey on Masked Image Modeling in Remote Sensing—0
MM811 Project Report: Cloud Detection and Removal in Satellite Images—0
A Conditional Generative Adversarial Network to Fuse Sar And Multispectral Optical Data For Cloud Removal From Sentinel-2 Images—0
Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal—0
Multi-temporal Sentinel-1 and -2 Data Fusion for Optical Image Simulation—0
On-board Change Detection for Resource-efficient Earth Observation with LEO Satellites—0
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