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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 26–50 of 56 papers

TitleStatusHype
When Cloud Removal Meets Diffusion Model in Remote Sensing—0
SAR-to-RGB Translation with Latent Diffusion for Earth Observation—0
Cross-Frequency Implicit Neural Representation with Self-Evolving Parameters—0
Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal—0
MIMRS: A Survey on Masked Image Modeling in Remote Sensing—0
Cloud Removal With PolSAR-Optical Data Fusion Using A Two-Flow Residual Network—0
Patch-GAN Transfer Learning with Reconstructive Models for Cloud Removal—0
Enhancing Scene Classification in Cloudy Image Scenarios: A Collaborative Transfer Method with Information Regulation Mechanism using Optical Cloud-Covered and SAR Remote Sensing ImagesCode0
Deeply Learned Robust Matrix Completion for Large-scale Low-rank Data Recovery—0
MRF-Net: An Infrared Remote Sensing Image Thin Cloud Removal Method With the Intra-Inter Coherent ConstraintCode0
Removing cloud shadows from ground-based solar imagery—0
Haar Nuclear Norms with Applications to Remote Sensing Imagery Restoration—0
Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection—0
Cloud Removal in Remote Sensing Using Sequential-Based Diffusion Models—0
On-board Change Detection for Resource-efficient Earth Observation with LEO Satellites—0
MM811 Project Report: Cloud Detection and Removal in Satellite Images—0
Cloud removal Using Atmosphere Model—0
Attention mechanism-based generative adversarial networks for cloud removal in Landsat images—0
Enhancing Satellite Imagery using Deep Learning for the Sensor To Shooter Timeline—0
Cloud Removal from Satellite Images—0
Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal—0
Thick Cloud Removal of Remote Sensing Images Using Temporal Smoothness and Sparsity-Regularized Tensor Optimization—0
Cloud Removal with Fusion of High Resolution Optical and SAR Images Using Generative Adversarial Networks—0
A Remote Sensing Image Dataset for Cloud RemovalCode0
Reading Industrial Inspection Sheets by Inferring Visual Relations—0
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