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Hyperspectral Image Denoising

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Showing 26–50 of 54 papers

TitleStatusHype
Rank-Enhanced Low-Dimensional Convolution Set for Hyperspectral Image Denoising—0
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising PackageCode1
DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors—0
Connections between Deep Equilibrium and Sparse Representation Models with Application to Hyperspectral Image Denoising—0
Hyperspectral Image Denoising Using Non-convex Local Low-rank and Sparse Separation with Spatial-Spectral Total Variation Regularization—0
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image RestorationCode1
Hyperspectral Mixed Noise Removal via Subspace Representation and Weighted Low-rank Tensor Regularization—0
Multi-modal and frequency-weighted tensor nuclear norm for hyperspectral image denoising—0
Hyperspectral Image Denoising with Log-Based Robust PCA—0
SSCAN: A Spatial-spectral Cross Attention Network for Hyperspectral Image Denoising—0
Hyperspectral Image Denoising Based On Multi-Stream Denoising Network—0
Hyperspectral Image Denoising and Anomaly Detection Based on Low-rank and Sparse RepresentationsCode0
Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse RepresentationsCode1
Hyperspectral Image Denoising via Multi-modal and Double-weighted Tensor Nuclear Norm—0
Hyperspectral image denoising based on global and non-local low-rank factorizationsCode1
Hyperspectral Image Denoising With Realistic DataCode1
SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising—0
Evolving Deep Convolutional Neural Networks for Hyperspectral Image Denoising—0
Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural NetworksCode1
Hyperspectral Image Denoising with Partially Orthogonal Matrix Vector Tensor Factorization—0
Hyperspectral Image Denoising via Global Spatial-Spectral Total Variation Regularized Nonconvex Local Low-Rank Tensor Approximation—0
Uncertainty Quantification for Hyperspectral Image Denoising Frameworks based on Low-rank Matrix ApproximationCode0
3D Quasi-Recurrent Neural Network for Hyperspectral Image DenoisingCode1
ADRN: Attention-based Deep Residual Network for Hyperspectral Image Denoising—0
Constrained low-tubal-rank tensor recovery for hyperspectral images mixed noise removal by bilateral random projections—0
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