SAR-to-optical image translation and cloud removal based on conditional generative adversarial networks: Literature survey, taxonomy, evaluation indicators, limits …
Due to the limitation of optical images that their waves cannot penetrate clouds, such images
always suffer from cloud contamination, which causes missing information and limitations for …
always suffer from cloud contamination, which causes missing information and limitations for …
UnCRtainTS: Uncertainty quantification for cloud removal in optical satellite time series
Clouds and haze often occlude optical satellite images, hindering continuous, dense
monitoring of the Earth's surface. Although modern deep learning methods can implicitly …
monitoring of the Earth's surface. Although modern deep learning methods can implicitly …
A critical review on multi-sensor and multi-platform remote sensing data fusion approaches: current status and prospects
Numerous remote sensing (RS) systems currently collect data about Earth and its
environments. However, each system provides limited data in terms of spatial resolution …
environments. However, each system provides limited data in terms of spatial resolution …
HS2P: Hierarchical spectral and structure-preserving fusion network for multimodal remote sensing image cloud and shadow removal
Optical remote sensing images are often contaminated by clouds and shadows, resulting in
missing data, which greatly hinders consistent Earth observation missions. Cloud and …
missing data, which greatly hinders consistent Earth observation missions. Cloud and …
Denoising diffusion probabilistic feature-based network for cloud removal in Sentinel-2 imagery
R **g, F Duan, F Lu, M Zhang, W Zhao - Remote Sensing, 2023 - mdpi.com
Cloud contamination is a common issue that severely reduces the quality of optical satellite
images in remote sensing fields. With the rapid development of deep learning technology …
images in remote sensing fields. With the rapid development of deep learning technology …
Blind single-image-based thin cloud removal using a cloud perception integrated fast Fourier convolutional network
Remote sensing images are frequently contaminated by clouds that often degrade the
performance of subsequent applications. Cloud removal, therefore, is a standard step in …
performance of subsequent applications. Cloud removal, therefore, is a standard step in …
Bridging remote sensors with multisensor geospatial foundation models
In the realm of geospatial analysis the diversity of remote sensors encompassing both
optical and microwave technologies offers a wealth of distinct observational capabilities …
optical and microwave technologies offers a wealth of distinct observational capabilities …
Former-CR: A transformer-based thick cloud removal method with optical and SAR imagery
S Han, J Wang, S Zhang - Remote Sensing, 2023 - mdpi.com
In the field of remote sensing, cloud and cloud shadow will result in optical remote sensing
image contamination, particularly high cloud cover, which will result in the complete loss of …
image contamination, particularly high cloud cover, which will result in the complete loss of …
Dehaze-TGGAN: Transformer-Guide Generative Adversarial Networks with Spatial-Spectrum Attention for Unpaired Remote Sensing Dehazing
Satellite imagery plays a critical role in target detection. However, the quality and usability of
optical remote sensing images can be severely compromised by atmospheric conditions …
optical remote sensing images can be severely compromised by atmospheric conditions …
HF-T2CR: High-fidelity thin and thick cloud removal in optical satellite images through SAR fusion
X Li, X Zhao, F Wang, P Ren - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Cloud removal can effectively address cloud contamination in optical remote sensing
images. But the simultaneous removal of both thin and thick clouds remains a significant …
images. But the simultaneous removal of both thin and thick clouds remains a significant …