Hyperspectral-Image-Denoising-Benchmark

A list of hyperspectral image denoising resources collected by Yongsen Zhao and Junjun Jiang.

Band-wise denoising methods

[BM3D] Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering, TIP2007, K. Dabov et al.
[WNNM] Weighted nuclear norm minimization with application to image denoising, CVPR2014, S. Gu et al.
[EPLL] From learning models of natural image patches to whole image restoration, ICCV2011, D. Zoran et al.

Multi-band based methods

[---Transform domain method---]

Wavelet-based hyperspectral image estimation, IGARSS2003, I. Atkinson et al.
Hyperspectral image denoising using 3D wavelets, IGARSS2013, B. Rasti et al.
A nonlocal transform-domain filter for volumetric data denoising and reconstruction, TIP2012, M. Maggioni et al.
Hyperspectral Image Denoising Using First Order Spectral Roughness Penalty in Wavelet Domain, JStars2014, B. Rasti et al.

[---Spatial domain methods---]

By adopting reasonable assumptions or priors, such as Global Correlation along Spetrum, Non-local Self Similarity (NSS) across space, Total Variation (TV), Non-local (Non-Local), Sparse Representation (SR), Low Rank (LR) models, Tensor models, etc., spatial domain based methods can well preserve the spatial and spectral characteristics.

[GCS and NSS] Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Denoising, ICCV2015, Ying Fu et al.
[GCS and NSS and Tensor] Decomposable nonlocal tensor dictionary learning for multispectral image denoising, CVPR2014, P. Yi et al. [Code]
[GCS and NSS] Multispectral images denoising by intrinsic tensor sparsity regularization, CVPR2016, Q. Xie et al. [Code]
[GCS] Denoising of hyperspectral images using the parafac model and statistical performance analysis, TGRS2012, X. F. Liu, et al.
[TV] Hyperspectral image denoising with cubic total variation model, ISPRS2012, H. Zhang et al.
[TV] Hyperspectral image denoising with a combined spatial and spectral hyperspectral total variation model, CJRS2014, G. Chen et al.
[SR] Spectral–Spatial Adaptive Sparse Representation for Hyperspectral Image Denoising, TGRS2016, T. Lu et al.
[SR] Noise removal from hyperspectral image with joint spectral-spatial distributed sparse representation, TGRS2016, J. Li et al.
[LR] Denoising and dimensionality reduction using multilinear tools for hyperspectral images, GRSL2008, N. Renard et al.
[LR] Hyperspectral image restoration using low-rank matrix recovery, TGRS2014, H. Zhang et al. [PDF][Code]
[LR] Hyperspectral Image Denoising via Noise-Adjusted Iterative Low-Rank Matrix Approximation, JStars2015, H. Zhang et al. [PDF][Code]
[LR] Hyperspectral image denoising via sparse representation and low-rank constraint, TGRS2015, Y. Zhao et al. [Code]
[LR and GCS] Hyperspectral Image Denoising Using Local Low-Rank Matrix Recovery and Global Spatial-Spectral Total Variation, JStars2015, H. Zhang et al. [PDF][Code]
[[LR and Tensor]] Hyper-Laplacian Regularized Unidirectional Low-rank Tensor Recovery for Multispectral Image Denoising, CVPR2017, Y. Chang et al. [Code]
[LR] Hyperspectral image restoration via iteratively regularized weighted Schatten p-norm minimization, TGRS2016, Y. Xie et al.
[LR and Tensor] Hyperspectral image restoration using low-rank tensor recovery, J-STARS2017, H. Fan et al.
[LR] Hyperspectral Image Restoration Using Low-Rank Representation on Spectral Difference Image, J-STARS2017, L. Sun et al. [Code]
[LR] Hyperspectral Image Denoising with Superpixel Segmentation and Low-Rank Representation, INS2017, F. Fan et al. [Code]
[LR] Fast hyperspectral image denoising and inpainting based on low-rank and sparse representations, J-STARS2018, L. Zhuang et al. [PDF][Code]
[LR and TV] A Novel Anisotropic Total Variation Regularized Low Rank Method for Hyperspectral Image Mixed Denoising, ISPRS International Journal of Geo-Information, 2018, L. Sun et al. [Code]
[LR] Fast Superpixel based Subspace Low Rank Learning Method for Hyperspectral Denoising. IEEE Access,2018, L. Sun et al. [Code]
[LR and TV and Tensor] Spatial-Spectral Total Variation Regularized Low-Rank Tensor Decomposition forv Hyperspectral Image Denoising, TGRS2018, H. Fan et al.
[LR] Hyperspectral Image Denoising via Minimizing the Partial Sum of Singular Values and Superpixel Segmentation, Neurocomputing2018, Y. Liu et al. [PDF]
[LR] Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising, arXiv2018, W. He et al. [Web][Pdf]
[Tensor] Color Image and Multispectral Image Denoising Using Block Diagonal Representation, arXiv2019, Zhaoming Kong et al. [PDF][Code]
Nonlocal Tensor-Ring Decomposition for Hyperspectral Image Denoising, IEEE TGRS 2019, Y. Chen et al.
Intracluster Structured Low-Rank Matrix Analysis Method for Hyperspectral Denoising, IEEE TGRS, Xiangtao Zheng et al.[PDF]
Hyperspectral Image Denoising by Fusing the Selected Related Bands, IEEE TGRS, Xiangtao Zheng et al.[PDF]
Nonlocal Low-Rank Regularized Tensor Decomposition for Hyperspectral Image Denoising, IEEE TGRS, Jize Xue et al.[PDF]
A Novel Rank Approximation Method for Mixture Noise Removal of Hyperspectral Images, IEEE TGRS, Hailiang Ye et al.[PDF]
A Low-Rank Tensor Dictionary Learning Method for Hyperspectral Image Denoising, IEEE TSP 2020, X. Gao et al.
Double Low-Rank Matrix Decomposition for Hyperspectral Image Denoising and Destriping, IEEE TGRS 2021, H. Zhang et al.
Hyperspectral Image Denoising Based on Global and Nonlocal Low-Rank Factorizations, IEEE TGRS 2021, L. Zhuang et al.
Deep spatio-spectral Bayesian posterior for hyperspectral image non-i.i.d. noise removal, ISPRS P&RS 2020, Q. Zhang et al.

Deep learning methods

Hyperspectral imagery denoising by deep learning with trainable nonlinearity function, GRSL2017, W. Xie et al.
Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network, TGRS2018, Q. Yuan et al. [Code]
HSI-DeNet: Hyperspectral Image Restoration via Convolutional Neural Network, TGRS2019, Yi Chang et al. [Web] [Pdf]
Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution, arxiv2019, Oleksii Sidorov et al. [Code] [Pdf]
Hybrid Noise Removal in Hyperspectral Imagery With a Spatial-Spectral Gradient Network, IEEE TGRS 2019, Qiang Zhang et al. [Code] [Pdf]
Deep Spatial-spectral Representation Learning for Hyperspectral Image Denoising, IEEE TCI 2019, Weisheng Dong et al. [Pdf][Code]
Hyperspectral image denoising via matrix factorization and deep prior regularization, IEEE TIP 2019, B. Li. [Pdf]
A 3-D Atrous Convolution Neural Network for Hyperspectral Image Denoising, IEEE TGRS 2019， Wei Liu et al.
Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural Networks, IEEE TGRS 2020, Han V. Nguyen et al.
A Single Model CNN for Hyperspectral Image Denoising, IEEE TGRS 2020, Alessandro Maffei et al.
Hyperspectral image restoration via CNN denoiser prior regularized low-rank tensor recovery, CVIU 2020, H. Zeng et al.
Hyperspectral Image Denoising via Clustering-Based Latent Variable in Variational Bayesian Framework, IEEE TGRS 2021, Peyman Azimpour et al.
Uncertainty Quantification of Hyperspectral Image Denoising Frameworks Based on Sliding-Window Low-Rank Matrix Approximation, IEEE TGRS 2021, J. Song et al.
Deep Spatial-Spectral Global Reasoning Network for Hyperspectral Image Denoising, IEEE TGRS 2021, X. Cao et al. [Code]
Hyperspectral Image Denoising Using a 3-D Attention Denoising Network, IEEE TGRS 2021, Q. Shi et al.
3-D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising, IEEE TNNLS 2021, K. Wei et al.

Other methods for Non-i.i.d. Noise

Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage, TGRS2006, H. Othman et al.
Hyperspectral image denoising employing a spectral–spatial adaptive total variation model, TGRS2012, Q. Yuan et al.
3-D nonlocal means filter with noise estimation for hyperspectral imagery denoising, IGRSS2013, Y. Qian et al.
Hyperspectral imagery restoration using nonlocal spectral-spatial structured sparse representation with noise estimation, JStars2013, Y. Qian et al.
Spectral–spatial kernel regularized for hyperspectral image denoising, IEE TGRS2015, Y. Yuan et al.
Denoising Hyperspectral Image with Non-i.i.d. Noise Structure, IEEE TCYB2017, Y. Chen et al. [PDF][Code]
Hyperspectral Image Denoising by Fusing the Selected Related Bandsx, IEEE TGRS2018, X. Zheng et al.
A Novel Rank Approximation Method for Mixture Noise Removal of Hyperspectral Images, IEEE TGRS2018, X. Zheng et al.

Databases

Image Quality Measurement

Peak Signal to Noise Ratio (PSNR)
Structural SIMilarity index (SSIM)
Feature SIMilarity index (FSIM)
Erreur Relative Globale Adimensionnelle de Synthèse (ERGAS)
Spectral Angle Mapper (SAM)

Since 2022/5/7

junjun-jiang/Hyperspectral-Image-Denoising-Benchmark

junjun-jiang

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