mlsanityData to 14 Oct 2026

Spatial-Spectral Transformer for Hyperspectral Image Denoising

arXiv 2211.14090 ↗First posted 25 Nov 2022cs.CV eess.IVcited by 34

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Abstract (arXiv)

Hyperspectral image (HSI) denoising is a crucial preprocessing procedure for the subsequent HSI applications. Unfortunately, though witnessing the development of deep learning in HSI denoising area, existing convolution-based methods face the trade-off between computational efficiency and capability to model non-local characteristics of HSI. In this paper, we propose a Spatial-Spectral Transformer (SST) to alleviate this problem. To fully explore intrinsic similarity characteristics in both spatial dimension and spectral dimension, we conduct non-local spatial self-attention and global spectral self-attention with Transformer architecture. The window-based spatial self-attention focuses on the spatial similarity beyond the neighboring region. While, spectral self-attention exploits the long-range dependencies between highly correlative bands. Experimental results show that our proposed method outperforms the state-of-the-art HSI denoising methods in quantitative quality and visual results.

Key facts. Cited by 34 papers in the map (data through 14 Oct 2026). Builds on 21 of its 51 references that are in the map. First posted on arXiv 25 Nov 2022.

Builds on

21 of 51 references.

References · 21

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9 more
  1. 2018Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Networkcited by 51
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  3. 20203D Quasi-Recurrent Neural Network for Hyperspectral Image Denoisingcited by 44
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  5. 2021Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representationscited by 39
  6. 2019Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolutioncited by 36
  7. 2021A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restorationcited by 34
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  9. 2018Hybrid Noise Removal in Hyperspectral Imagery With a Spatial-Spectral Gradient Networkcited by 14

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 7; 2024: 12; 2025: 11; 2026: 4.

34 papers.

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  1. 2024HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Modelcited by 73
  2. 2024HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Modelscited by 39
  3. 2023DDS2M: Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restorationcited by 33
  4. 2024SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoisingcited by 20
  5. 2025HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagerycited by 17
  6. 2023Hybrid Spectral Denoising Transformer with Guided Attentioncited by 16
  7. 2024HINT: High-quality INPainting Transformer with Mask-Aware Encoding and Enhanced Attentioncited by 11
  8. 2023A Comparison of Image Denoising Methodscited by 7
  9. 2024HSIDMamba: Exploring Bidirectional State-Space Models for Hyperspectral Denoisingcited by 7
  10. 2024PromptHSI: Universal Hyperspectral Image Restoration with Vision-Language Modulated Frequency Adaptationcited by 7
  11. 2025Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapsecited by 7
  12. 2023Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformercited by 6
22 more
  1. 2024A Hybrid Transformer-Mamba Network for Single Image Derainingcited by 6
  2. 2023Deep Diversity-Enhanced Feature Representation of Hyperspectral Imagescited by 5
  3. 2024HDMba: Hyperspectral Remote Sensing Imagery Dehazing with State Space Modelcited by 5
  4. 2024Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Imagecited by 4
  5. 2026HADAR-Based Thermal Infrared Hyperspectral Image Restorationcited by 4
  6. 2024Hybrid Spatial-spectral Neural Network for Hyperspectral Image Denoisingcited by 2
  7. 2025Iterative Low-rank Network for Hyperspectral Image Denoisingcited by 2
  8. 2024Filterless Snapshot Hyperspectral Imaging using Guided Patch Diffusioncited by 1
  9. 2025AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolutioncited by 1
  10. 2025ACMamba: Fast Unsupervised Anomaly Detection via An Asymmetrical Consensus State Space Modelcited by 1
  11. 2025Degradation-Aware Metric Prompting for Hyperspectral Image Restorationcited by 1
  12. 2025Next-Scale Prediction: A Self-Supervised Approach for Real-World Image Denoisingcited by 1
  13. 2026Leveraging pretrained RGB denoisers for hyperspectral image restorationcited by 1
  14. 2023HIDFlowNet: A Flow-Based Deep Network for Hyperspectral Image Denoisingcited by 0
  15. 2023Learning Exhaustive Correlation for Spectral Super-Resolution: Where Spatial-Spectral Attention Meets Linear Dependencecited by 0
  16. 2024Beyond the Visible: Jointly Attending to Spectral and Spatial Dimensions with HSI-Diffusion for the FINCH Spacecraftcited by 0
  17. 2025Equal is Not Always Fair: A New Perspective on Hyperspectral Representation Non-Uniformitycited by 0
  18. 2025A TRPCA-Inspired Deep Unfolding Network for Hyperspectral Image Denoising via Thresholded t-SVD and Top-K Sparse Transformercited by 0
  19. 2025Physical Degradation Model-Guided Interferometric Hyperspectral Reconstruction with Unfolding Transformercited by 0
  20. 2025Deep Equilibrium Convolutional Sparse Coding for Hyperspectral Image Denoisingcited by 0
  21. 2026R2H-Diff: Guided Spectral Diffusion Model for RGB-to-Hyperspectral Reconstructioncited by 0
  22. 2026Spectrum Aware Illumination Estimation Using Multispectral Imagecited by 0