mlsanityData to 7 Oct 2026

A Comprehensive Survey for Hyperspectral Image Classification: The Evolution from Conventional to Transformers and Mamba Models

arXiv 2404.14955 ↗First posted 23 Apr 2024cs.CVcited by 19

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

Abstract (arXiv)

Hyperspectral Image Classification (HSC) presents significant challenges owing to the high dimensionality and intricate nature of Hyperspectral (HS) data. While traditional Machine Learning (TML) approaches have demonstrated effectiveness, they often encounter substantial obstacles in real-world applications, including the variability of optimal feature sets, subjectivity in human-driven design, inherent biases, and methodological limitations. Specifically, TML suffers from the curse of dimensionality, difficulties in feature selection and extraction, insufficient consideration of spatial information, limited robustness against noise, scalability issues, and inadequate adaptability to complex data distributions. In recent years, Deep Learning (DL) techniques have emerged as robust solutions to address these challenges. This survey offers a comprehensive overview of current trends and future prospects in HSC, emphasizing advancements from DL models to the increasing adoption of Transformer and Mamba Model architectures. We systematically review key concepts, methodologies, and state-of-the-art approaches in DL for HSC. Furthermore, we investigate the potential of Transformer-based models and the Mamba Model in HSC, detailing their advantages and challenges. Emerging trends in HSC are explored, including in-depth discussions on Explainable AI and Interoperability concepts, alongside Diffusion Models for image denoising, feature extraction, and image fusion. Comprehensive experimental results were conducted on three HS datasets to substantiate the efficacy of various conventional DL models and Transformers. Additionally, we identify several open challenges and pertinent research questions in the field of HSC. Finally, we outline future research directions and potential applications aimed at enhancing the accuracy and efficiency of HSC.

Key facts. Cited by 19 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 68 of its 475 references that are in the map. First posted on arXiv 23 Apr 2024.

Builds on

68 of 475 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024SpectralMamba: Efficient Mamba for Hyperspectral Image Classification12 Apr

Other references · 67

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  4. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  5. 2019On the Variance of the Adaptive Learning Rate and Beyondcited by 763
  6. 2023SpectralGPT: Spectral Remote Sensing Foundation Modelcited by 250
  7. 2021SpectralFormer: Rethinking Hyperspectral Image Classification with Transformerscited by 168
  8. 2022UIU-Net: U-Net in U-Net for Infrared Small Object Detectioncited by 124
  9. 2019Deep Learning for Hyperspectral Image Classification: An Overviewcited by 121
  10. 2020Graph Convolutional Networks for Hyperspectral Image Classificationcited by 113
  11. 2020Gradient Centralization: A New Optimization Technique for Deep Neural Networkscited by 82
  12. 2018An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixingcited by 65
38 more
  1. 2017Hyperspectral Image Restoration via Total Variation Regularized Low-rank Tensor Decompositioncited by 61
  2. 2023Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networkscited by 55
  3. 2021Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future Prospectscited by 49
  4. 2021Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Modelcited by 43
  5. 2020Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)cited by 36
  6. 2021Deep Learning for UAV-based Object Detection and Tracking: A Surveycited by 33
  7. 2023DDS2M: Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restorationcited by 32
  8. 2019Cascaded Recurrent Neural Networks for Hyperspectral Image Classificationcited by 31
  9. 2021Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolutioncited by 31
  10. 2023B-cos Alignment for Inherently Interpretable CNNs and Vision Transformerscited by 31
  11. 2023HSR-Diff:Hyperspectral Image Super-Resolution via Conditional Diffusion Modelscited by 31
  12. 2019diffGrad: An Optimization Method for Convolutional Neural Networkscited by 29
  13. 2023SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion Modelscited by 28
  14. 2020FsNet: Feature Selection Network on High-dimensional Biological Datacited by 23
  15. 2022Deep Hyperspectral Unmixing using Transformer Networkcited by 22
  16. 2019Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Networkcited by 20
  17. 2019ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Featurescited by 18
  18. 2022Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel Fusioncited by 18
  19. 2019Learnable Manifold Alignment (LeMA) : A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classificationcited by 17
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50 most cited of 67 All 67 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 11.

19 papers.

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  1. 2025EnergyFormer: Energy Attention with Fourier Embedding for Hyperspectral Image Classificationcited by 4
  2. 2025Hybrid State-Space and GRU-based Graph Tokenization Mamba for Hyperspectral Image Classificationcited by 1
  3. 2025Hyperspectral Imagingcited by 1
  4. 2025Deep Learning for Clouds and Cloud Shadow Segmentation in Methane Satellite and Airborne Imaging Spectroscopycited by 1
  5. 2025Balanced Diffusion-Guided Fusion for Multimodal Remote Sensing Classificationcited by 1
  6. 20263D Fourier-based Global Feature Extraction for Hyperspectral Image Classificationcited by 1
  7. 2026High-Dimensional Noise to Low-Dimensional Manifolds: A Manifold-Space Diffusion Framework for Degraded Hyperspectral Image Classificationcited by 1
  8. 2025Dynamic Memory Transformer for Hyperspectral Image Classificationcited by 0
  9. 2025Diffusion-Denoised Hyperspectral Gaussian Splattingcited by 0
  10. 2025Spatial-Temporal-Spectral Mamba with Sparse Deformable Token Sequence for Enhanced MODIS Time Series Classificationcited by 0
  11. 2026Unbalanced Optimal Transport Dictionary Learning for Unsupervised Hyperspectral Image Clusteringcited by 0
  12. 2026Bidirectional Cross-Attention Fusion of High-Resolution RGB and Low-Resolution Hyperspectral Inputs for Multimodal Semantic Segmentationcited by 0
7 more
  1. 2026Cosine-Normalized Attention for Hyperspectral Image Classificationcited by 0
  2. 2026Deep Spatially-Regularized and Superpixel-Based Diffusion Learning for Unsupervised Hyperspectral Image Clusteringcited by 0
  3. 2026Survey on Disaster Management Datasets for Remote Sensing Based Emergency Applicationscited by 0
  4. 2026DAPGNet: Dynamic Adaptive Physics-Guided Graph Diffusion Network for Hyperspectral Image Classificationcited by 0
  5. 2026Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Predictioncited by 0
  6. 2026Fermat Active Laplace Learning for Semi-Supervised Hyperspectral Image Classificationcited by 0
  7. 2026Topology-Aware Neighborhood Learning for Source-Free Cross-Scene Hyperspectral Image Classificationcited by 0

Similar, not cited

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  1. 2026ConvVitMamba: Efficient Multiscale Convolution, Transformer, and Mamba-Based Sequence modelling for Hyperspectral Image Classification
  2. 2024WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification
  3. 2025MVNet: Hyperspectral Remote Sensing Image Classification Based on Hybrid Mamba-Transformer Vision Backbone Architecture
  4. 2026MSCM-net: A hyperspectral image classiffcation method based on multi-scale convolution and Mamba
  5. 2026VP-Hype: A Hybrid Mamba-Transformer Framework with Visual-Textual Prompting for Hyperspectral Image Classification
  6. 20243DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification
  7. 2025MambaHSI: Spatial-Spectral Mamba for Hyperspectral Image Classification
  8. 2026Hyperspectral Image Models: Technical Report