Hyperspectral Image Denoising

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

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Most implemented papers archive 2025-07-28

26 shown of 26 papers with code (54 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Spatial-Spectral Transformer for Hyperspectral Image Denoising
  25 Nov 2022 3 repositories listed Syntology ran 0 of 2 samples · 2 unverified · 2 pointer-only (licence)
  Hyperspectral image (HSI) denoising is a crucial preprocessing procedure for the subsequent HSI applications.
• A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration
  18 Nov 2021 2 repositories listed
  Hyperspectral imaging offers new perspectives for diverse applications, ranging from the monitoring of the environment using airborne or satellite remote sensing, precision farming, food safety, planetary exploration,…
• Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representations
  11 Mar 2021 2 repositories listed
  This paper introduces two very fast and competitive hyperspectral image (HSI) restoration algorithms: fast hyperspectral denoising (FastHyDe), a denoising algorithm able to cope with Gaussian and Poissonian noise, and…
• 3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising
  10 Mar 2020 2 repositories listed
  In this paper, we propose an alternating directional 3D quasi-recurrent neural network for hyperspectral image (HSI) denoising, which can effectively embed the domain knowledge -- structural spatio-spectral correlation…
• Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising
  11 Dec 2018 2 repositories listed
  This is done by first learning a low-dimensional projection and the related reduced image from the noisy HSI.
• Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network
  1 Jun 2018 2 repositories listed
  Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the performance of the subsequent HSI interpretation and applications.
• Pan-denoising: Guided Hyperspectral Image Denoising via Weighted Represent Coefficient Total Variation
  8 Jul 2024 1 repository listed
  This paper introduces a novel paradigm for hyperspectral image (HSI) denoising, which is termed \textit{pan-denoising}.
• Beyond the Visible: Jointly Attending to Spectral and Spatial Dimensions with HSI-Diffusion for the FINCH Spacecraft
  15 Jun 2024 1 repository listed
  This paper presents a novel approach to hyperspectral image denoising using latent diffusion models that integrate spatial and spectral information.
• SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising
  2 May 2024 1 repository listed
  Long-range spatial-spectral correlation modeling is beneficial for HSI denoising but often comes with high computational complexity.
• Spatio-Spectral Structure Tensor Total Variation for Hyperspectral Image Denoising and Destriping
  4 Apr 2024 1 repository listed
  This paper proposes a novel regularization method, named Spatio-Spectral Structure Tensor Total Variation (S3TTV), for denoising and destriping of hyperspectral (HS) images.
• Eigen-CNN: Eigenimages Plus Eigennoise Level Maps Guided Network for Hyperspectral Image Denoising
  19 Mar 2024 1 repository listed
  Experimental results on both simulated and real HSIs demonstrate the effectiveness of our trained Eigen-CNN compared with state-of-the-art HSI denoising methods.
• Hybrid Convolutional and Attention Network for Hyperspectral Image Denoising
  15 Mar 2024 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  To enhance the modeling of both global and local features, we have devised a convolution and attention fusion module aimed at capturing long-range dependencies and neighborhood spectral correlations.
• Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformer
  31 Dec 2023 1 repository listed
  This block consists of a spatial branch and a spectral branch.
• Hyperspectral Image Denoising via Self-Modulating Convolutional Neural Networks
  15 Sep 2023 1 repository listed
  At the core of the model lies a novel block, which we call spectral self-modulating residual block (SSMRB), that allows the network to transform the features in an adaptive manner based on the adjacent spectral data,…
• Multi-scale Adaptive Fusion Network for Hyperspectral Image Denoising
  19 Apr 2023 1 repository listed
  Two key components contribute to improving the hyperspectral image denoising: A progressively multiscale information aggregation network and a co-attention fusion module.
• Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising
  3 Apr 2023 1 repository listed
  In this paper, we address these issues by proposing a spectral enhanced rectangle Transformer, driving it to explore the non-local spatial similarity and global spectral low-rank property of HSIs.
• Hybrid Spectral Denoising Transformer with Guided Attention
  16 Mar 2023 1 repository listed Syntology ran 0 of 5 samples · 5 unverified
  Challenges in adapting transformer for HSI arise from the capabilities to tackle existing limitations of CNN-based methods in capturing the global and local spatial-spectral correlations while maintaining efficiency and…
• Mixed Attention Network for Hyperspectral Image Denoising
  27 Jan 2023 1 repository listed
  However, existing methods show limitations in exploring the spectral correlations across different bands and feature interactions within each band.
• Deep Sparse and Low-Rank Prior for Hyperspectral Image Denoising
  28 Sep 2022 1 repository listed
  The combination of a sparse and low-rank prior with a DIP views the CNN-based denoising method similar to a model-based method, inheriting the advantages of both model-based and CNN-based methods.
• Deep Plug-and-Play Prior for Hyperspectral Image Restoration
  17 Sep 2022 1 repository listed
  Deep-learning-based hyperspectral image (HSI) restoration methods have gained great popularity for their remarkable performance but often demand expensive network retraining whenever the specifics of task changes.
• HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package
  14 Apr 2022 1 repository listed
  Furthermore, we present a method for training DNNs for denoising HSIs which are not spatially related to the training dataset, i.
• Hyperspectral Image Denoising and Anomaly Detection Based on Low-rank and Sparse Representations
  12 Mar 2021 1 repository listed
  Hyperspectral imaging measures the amount of electromagnetic energy across the instantaneous field of view at a very high resolution in hundreds or thousands of spectral channels.
• Hyperspectral image denoising based on global and non-local low-rank factorizations
  8 Jan 2021 1 repository listed
  The ever-increasing spectral resolution of hyperspectral images (HSIs) is often obtained at the cost of a decrease in the signal-to-noise ratio of the measurements, thus calling for effective denoising techniques.
• Hyperspectral Image Denoising With Realistic Data
  1 Jan 2021 1 repository listed
  On the other hand, we propose an accurate HSI noise model which matches the distribution of real data well and can be employed to synthesize realistic dataset.
• Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural Networks
  23 Jul 2020 1 repository listed
  Since SURE is an unbiased estimate of the mean squared error (MSE) of an estimator, training a CNN using the SURE loss can yield similar results as using the MSE with ground truth in supervised learning.
• Uncertainty Quantification for Hyperspectral Image Denoising Frameworks based on Low-rank Matrix Approximation
  23 Apr 2020 1 repository listed
  Sliding-window based low-rank matrix approximation (LRMA) is a technique widely used in hyperspectral images (HSIs) denoising or completion.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.