mlsanityData to 7 Oct 2026

SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising

arXiv 2405.01726 ↗First posted 2 May 2024eess.IV cs.CV cs.LGcited by 20

On the map: State-space sequence models (S4, Mamba) → Hyperspectral image analysis with Mamba

Abstract (arXiv)

Denoising is a crucial preprocessing step for hyperspectral images (HSIs) due to noise arising from intra-imaging mechanisms and environmental factors. Long-range spatial-spectral correlation modeling is beneficial for HSI denoising but often comes with high computational complexity. Based on the state space model (SSM), Mamba is known for its remarkable long-range dependency modeling capabilities and computational efficiency. Building on this, we introduce a memory-efficient spatial-spectral UMamba (SSUMamba) for HSI denoising, with the spatial-spectral continuous scan (SSCS) Mamba being the core component. SSCS Mamba alternates the row, column, and band in six different orders to generate the sequence and uses the bidirectional SSM to exploit long-range spatial-spectral dependencies. In each order, the images are rearranged between adjacent scans to ensure spatial-spectral continuity. Additionally, 3D convolutions are embedded into the SSCS Mamba to enhance local spatial-spectral modeling. Experiments demonstrate that SSUMamba achieves superior denoising results with lower memory consumption per batch compared to transformer-based methods. The source code is available at https://github.com/lronkitty/SSUMamba.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Placed in Hyperspectral image analysis with Mamba, one of 10 directions in State-space sequence models (S4, Mamba). Builds on 34 of its 79 references that are in the map. First posted on arXiv 2 May 2024.

Builds on

34 of 79 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024HSIDMamba: Exploring Bidirectional State-Space Models for Hyperspectral Denoising15 Apr

Other references · 33

  1. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,616
  2. 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,424
  3. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
  4. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  5. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  6. 2021Video Swin Transformercited by 1,090
  7. 2024Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Modelcited by 1,051
  8. 2022Exploring CLIP for Assessing the Look and Feel of Imagescited by 974
  9. 2024VMamba: Visual State Space Modelcited by 955
  10. 2024U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentationcited by 412
  11. 2024Jamba: A Hybrid Transformer-Mamba Language Modelcited by 390
  12. 2024MambaIR: A Simple Baseline for Image Restoration with State-Space Modelcited by 349
21 more
  1. 2024VideoMamba: State Space Model for Efficient Video Understandingcited by 325
  2. 2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 220
  3. 2021SpectralFormer: Rethinking Hyperspectral Image Classification with Transformerscited by 168
  4. 2021Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstructioncited by 110
  5. 2024Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understandingcited by 106
  6. 2024VmambaIR: Visual State Space Model for Image Restorationcited by 90
  7. 2024ZigMa: A DiT-style Zigzag Mamba Diffusion Modelcited by 84
  8. 2018Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Networkcited by 51
  9. 20203D Quasi-Recurrent Neural Network for Hyperspectral Image Denoisingcited by 44
  10. 2020Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restorationcited by 43
  11. 2021Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representationscited by 39
  12. 2018Material Based Object Tracking in Hyperspectral Videos: Benchmark and Algorithmscited by 36
  13. 2023Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoisingcited by 35
  14. 2021A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restorationcited by 34
  15. 2022Spatial-Spectral Transformer for Hyperspectral Image Denoisingcited by 34
  16. 2022Fast and Memory-Efficient Network Towards Efficient Image Super-Resolutioncited by 27
  17. 2017Denoising Hyperspectral Image with Non-i.i.d. Noise Structurecited by 23
  18. 2023Hybrid Spectral Denoising Transformer with Guided Attentioncited by 16
  19. 2024HSIMamba: Hyperpsectral Imaging Efficient Feature Learning with Bidirectional State Space for Classificationcited by 14
  20. 2022A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximationcited by 7
  21. 2023Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformercited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 6; 2026: 6.

20 papers.

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  1. 2024HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Modelcited by 72
  2. 2024QMambaBSR: Burst Image Super-Resolution with Query State Space Modelcited by 27
  3. 2025Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restorationcited by 27
  4. 2024MambaCSR: Dual-Interleaved Scanning for Compressed Image Super-Resolution With SSMscited by 14
  5. 2024S3Mamba: Arbitrary-Scale Super-Resolution via Scaleable State Space Modelcited by 12
  6. 2024DenoMamba: A fused state-space model for low-dose CT denoisingcited by 11
  7. 2025Vision Mamba in Remote Sensing: A Comprehensive Survey of Techniques, Applications and Outlookcited by 6
  8. 2024SITSMamba for Crop Classification based on Satellite Image Time Seriescited by 4
  9. 2024CT-Mamba: A Hybrid Convolutional State Space Model for Low-Dose CT Denoisingcited by 4
  10. 2025HSRMamba: Contextual Spatial-Spectral State Space Model for Single Image Hyperspectral Super-Resolutioncited by 3
  11. 2026Scalable neural pushbroom architectures for real-time denoising of hyperspectral images onboard satellitescited by 1
  12. 2026HSI-VAR: Rethinking Hyperspectral Restoration through Spatial-Spectral Visual Autoregressioncited by 1
8 more
  1. 2024Beyond the Visible: Jointly Attending to Spectral and Spatial Dimensions with HSI-Diffusion for the FINCH Spacecraftcited by 0
  2. 2025ECP-Mamba: An Efficient Multi-scale Self-supervised Contrastive Learning Method with State Space Model for PolSAR Image Classificationcited by 0
  3. 2025Cancer cytoplasm segmentation in hyperspectral cell image with data augmentationcited by 0
  4. 2025Deep Equilibrium Convolutional Sparse Coding for Hyperspectral Image Denoisingcited by 0
  5. 2026HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generationcited by 0
  6. 2026Quantum Enchanced Multi-Scale CNN with Bi-directional Mamba for Crop Field Analysiscited by 0
  7. 2026State Space Models Meet Remote Sensing: A Surveycited by 0
  8. 2026AXS-Net: Interpretable Deep Unfolding for Hyperspectral Image Denoising via Spectral Basis Unmixing and Structured Noise Refinementcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024S2Mamba: A Spatial-spectral State Space Model for Hyperspectral Image Classification
  2. 20243DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification
  3. 2025HSRMamba: Efficient Wavelet Stripe State Space Model for Hyperspectral Image Super-Resolution
  4. 2024HDMba: Hyperspectral Remote Sensing Imagery Dehazing with State Space Model
  5. 2024SpectralMamba: Efficient Mamba for Hyperspectral Image Classification
  6. 2024WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification
  7. 2024Dual Hyperspectral Mamba for Efficient Spectral Compressive Imaging
  8. 2024Spectral-Spatial Mamba for Hyperspectral Image Classification