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STFDiff: Remote sensing image spatiotemporal fusion with diffusion models
Spatiotemporal fusion (STF) methods aim to blend satellite images with different spatial and
temporal resolutions to support more frequent and precise monitoring. In the past decades …
temporal resolutions to support more frequent and precise monitoring. In the past decades …
Thick cloud removal in multitemporal remote sensing images via low-rank regularized self-supervised network
The existence of thick clouds covers the comprehensive Earth observation of optical remote
sensing images (RSIs). Cloud removal is an effective and economical preprocessing step to …
sensing images (RSIs). Cloud removal is an effective and economical preprocessing step to …
An interpretable and flexible fusion prior to boost hyperspectral imaging reconstruction
Hyperspectral image (HSI) reconstruction from the compressed measurement captured by
the coded aperture snapshot spectral imager system remains a hot topic. Recently, deep …
the coded aperture snapshot spectral imager system remains a hot topic. Recently, deep …
An unsupervised dehazing network with hybrid prior constraints for hyperspectral image
Haze pollution in hyperspectral images (HSIs) leads to surface information lack and image
clarity degradation, which seriously affects the performance of subsequent image …
clarity degradation, which seriously affects the performance of subsequent image …
Fast Large-Scale Hyperspectral Image Denoising via Non-Iterative Low-Rank Subspace Representation
Denoising of hyperspectral image (HSI) is challenging, especially when dealing with large-
scale data. Model-based methods show promise in HSI denoising due to their good …
scale data. Model-based methods show promise in HSI denoising due to their good …
Three-Dimension Spatial-Spectral Attention Transformer for Hyperspectral Image Denoising
Hyperspectral image (HSI) denoising is a crucial step for its subsequent applications. In this
article, we propose TDSAT, a 3-D spatial-spectral attention Transformer model designed to …
article, we propose TDSAT, a 3-D spatial-spectral attention Transformer model designed to …
Latent diffusion enhanced rectangle transformer for hyperspectral image restoration
The restoration of hyperspectral image (HSI) plays a pivotal role in subsequent
hyperspectral image applications. Despite the remarkable capabilities of deep learning …
hyperspectral image applications. Despite the remarkable capabilities of deep learning …
Degradation estimation recurrent neural network with local and non-local priors for compressive spectral imaging
In the coded aperture snapshot spectral imaging (CASSI) system, deep unfolding networks
(DUNs) have demonstrated excellent performance in recovering 3-D hyperspectral images …
(DUNs) have demonstrated excellent performance in recovering 3-D hyperspectral images …
CroDoSR: Tensor cross-domain rank for hyperspectral image super-resolution
Hyperspectral image super-resolution (HSI SR) aims to combine the detailed spectral
information of hyperspectral images with the spatial resolution of multispectral images, thus …
information of hyperspectral images with the spatial resolution of multispectral images, thus …
Cyclic tensor singular value decomposition with applications in low-rank high-order tensor recovery
Y Zhang, Z Tu, J Lu, C Xu, MK Ng - Signal Processing, 2024 - Elsevier
The rapid advancements in emerging technologies have increased the demand for recovery
tasks involving high-dimensional data with complex structures. Effectively utilizing tensor …
tasks involving high-dimensional data with complex structures. Effectively utilizing tensor …