MambaHSI: Spatial-Spectral Mamba for Hyperspectral Image Classification

Yapeng Li, Yong Luo, Lefei Zhang, Zengmao Wang*, Bo Du*

📝 Introduction

• To our best knowledge, the MambaHSI is the first image-level hyperspectral image classification model based on SSM, which can simultaneously model long-range interaction of whole image and integrate spatial and spectral image information.
• MambaHSI demonstrates the great potential of Mamba to be the next-generation backbone for hyperspectral image models.

🚀 Getting Started

Installation

conda create -n MambaHSI_env python=3.9
conda activate MambaHSI_env
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia
pip install packaging==24.0
pip install triton==2.2.0
pip install mamba-ssm==1.2.0
pip install spectral
pip install scikit-learn==1.4.1.post1
pip install calflops

Data Preparation

The dataset can download Google Drive and BaiduNetdisk.

data
└── UP/
    ├── PaviaU.mat 
    └── PaviaU_gt.mat
    ...
└── Houston/
    ├── Houston.mat 
    └── Houston_GT.mat
    ...
└── HanChuan/
    ├── WHU_Hi_HanChuan.mat 
    └── WHU_Hi_HanChuan_gt.mat
    ...
└── HongHu/  
    ├── WHU_Hi_HongHu.npy
    └── WHU_Hi_HongHu_gt.npy

Training:

python train_MambaHSI.py --dataset_index 0
python train_MambaHSI.py --dataset_index 1
python train_MambaHSI.py --dataset_index 2
python train_MambaHSI.py --dataset_index 3

🎖️ Main Results

Pavia University Results

Houston Results

HanChuan Results

HongHu Results

Citation

If you find this project helpful for your research, please kindly consider citing our paper and give this repo ⭐️:

@ARTICLE{MambaHSI_TGRS24,
  author={Li, Yapeng and Luo, Yong and Zhang, Lefei and Wang, Zengmao and Du, Bo},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={MambaHSI: Spatial-Spectral Mamba for Hyperspectral Image Classification}, 
  year={2024},
  volume={},
  number={},
  pages={1-16},
  keywords={Hyperspectral Image Classification;Mamba;State Space Models;Transformer},
  doi={10.1109/TGRS.2024.3430985}}

Acknowledgement

Part of our MambaHSI framework is referred to CVSSN and SSFCN. We thank all the contributors for open-sourcing.