Li-ZK / FSCF-SSL-2023

Few-shot Hyperspectral Image Classification with Self-supervised Learning

This is a code demo for the paper "Few-shot Hyperspectral Image Classification with Self-supervised Learning" Zhaokui Li, Hui Guo, Yushi Chen, Cuiwei Liu, Qian Du, Zhuoqun Fang, and Yan Wang, Few-shot Hyperspectral Image Classification with Self-supervised Learning, IEEE Transactions on Geoscience and Remote Sensing.

Requirements

• CUDA = 11.1
• Python = 3.9
• Pytorch = 1.8.0
• sklearn = 1.0.1
• numpy = 1.21.2

Datasets

You can download the hyperspectral datasets in mat format at: http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes, and move the files to ./datasets folder. You can download the WHU-Hi-HanChuan hyperspectral dataset from the following link. Link: https://pan.baidu.com/s/1IfHYp-WL6dDDpjO1AU_Law?pwd=b63e Extract code:b63e

The mini-ImageNet data sets can be downloaded from the following link: Link: https://pan.baidu.com/s/1Mn1en9EhfFvE-i62YnbwhQ Extract code: 54DO

An example dataset folder has the following structure:

datasets
├── IP
│   ├── indian_pines_corrected.mat
│   ├── indian_pines_gt.mat
└── paviaU
│   ├── paviaU.mat
│   ├── paviaU_gt.mat
└── HC
│   ├── WHU_Hi_HanChuan.mat
│   ├── WHU_Hi_HanChuan(15%)_gt.mat
└── Salinas
│   ├── Salinas_corrected.mat
│   ├── salinas_gt.mat
└── miniImagenet
│   ├── 
│   ├── 

Usage:

Take FSCF-SSL method :

1. Download the required data set and move to folder./datasets.
2. To run the file, you need to download the VGG pre-training weights file (vgg16_bn-6c64b313.pth). The VGG pre-training weight file can be downloadfrom the following link: Link: https://pan.baidu.com/s/1iOYOaiWXibaaIpapb_GFsQ Extract code：0tdu
3. Taking 5 labeled samples per class as an example, run FSCF-SSL.py