This is the code for CSR-Net: Camera Spectral Response Network for Dimensionality Reduction and Classification in Hyperspectral Imagery, Remote Sensing 2020, by Yunhao Zou, Ying Fu, Yinqiang Zheng and Wei Li.
In this work, we present a CNN architecture called CSR-Net for hyperspectral image classification. Our model can achieve the optimal camera spectral response (CSR) functions for HSI classification. More importantly, the learned CSR can be directly used to reduce data dimensions when capturing images as well as guarantee the classification accuracy.
- python 3.6
- pytorch 1.8.0
- numpy
- scikit-learn
- matplotlib
Please run sh train.sh
for training and testing.
If you find this work useful for your research, please cite:
@article{zou2020csr,
title={CSR-Net: Camera Spectral Response Network for Dimensionality Reduction and Classification in Hyperspectral Imagery},
author={Zou, Yunhao and Fu, Ying and Zheng, Yinqiang and Li, Wei},
journal={Remote Sensing},
volume={12},
number={20},
pages={3294},
year={2020},
}
This codes are inspired by pResNet-HSI and DANet