MCNN-based_HSI_Classification

Papers

• MCNN-CP: Hyperspectral Image Classification Using Mixed Convolutions and Covariance Pooling (TGARS 2021) paper and source_code
• Oct-MCNN-HS: 3D Octave and 2D Vanilla Mixed Convolutional Neural Network for Hyperspectral Image Classification With Limited Samples (Remote Sensing,2021) paper

1. Environment setup

This code has been tested on on a personal laptop with Intel i7-9750H 2.6-GHz processor, 32-GB RAM, and an NVIDIA GTX1650 graphic card, Python 3.6, tensorflow_gpu-1.14.0, Keras-2.2.4, CUDA 10.0, cuDNN 7.6. Please install related libraries before running this code:

pip install -r requirements.txt

2. Download the datesets:

• IP: Indian Pines corrected and Indian Pines gt
• UH: University of Houston 2018
• UP: University of Pavia corrected and University of Pavia gt
• SA: Salinas Scene corrected and Salinas Scene gt

and put them into data directory.

3. Download the models (loading models):

• models code:

and put them into models directory.

4. Download the pretrained_models (loading model parameters):

• IP: Indian Pines code:
• UH: University of Houston code:
• UP: University of Pavia code:
• SA: Salinas Scene code:

and put them into pretrained_models directory.

5. Test

python validate.py                
--dataset IP                       # dataset_name
--model MCNN-CP                    # model_name
--ratio 0.99                       # test_ratio

The testing result will be saved in the classification_report.txt.

6. Cite

If you use MCNN-CP in your work please cite our paper:

• BibTex：

  @ARTICLE{9103280, author={J. {Zheng} and Y. {Feng} and C. {Bai} and J. {Zhang}}, journal={IEEE Transactions on Geoscience and Remote Sensing}, title={Hyperspectral Image Classification Using Mixed Convolutions and Covariance Pooling}, year={2021}, volume={59}, number={1}, pages={522-534}, doi={10.1109/TGRS.2020.2995575}}, }

• Plane Text：

  J. Zheng, Y. Feng, C. Bai and J. Zhang, "Hyperspectral Image Classification Using Mixed Convolutions and Covariance Pooling," in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 1, pp. 522-534, Jan. 2021, doi: 10.1109/TGRS.2020.2995575.

If you use Oct-MCNN-PS in your work please cite our paper:

• BibTex：

  @Article{rs13214407, AUTHOR = {Feng, Yuchao and Zheng, Jianwei and Qin, Mengjie and Bai, Cong and Zhang, Jinglin}, TITLE = {3D Octave and 2D Vanilla Mixed Convolutional Neural Network for Hyperspectral Image Classification with Limited Samples}, JOURNAL = {Remote Sensing}, VOLUME = {13}, YEAR = {2021}, NUMBER = {21}, ARTICLE-NUMBER = {4407}, URL = {https://www.mdpi.com/2072-4292/13/21/4407}, ISSN = {2072-4292}, DOI = {10.3390/rs13214407} }