MoG-DCN

This repository contains the Pytorch codes of paper "Model-Guided Deep Hyperspectral Image Super-resolution"

Using sf=8 and trined /tested on CAVE as an example ,I will introduce the usage of this code
Download CAVE , Harvard and WV2

Prepare the training data and the test data

1. Divide the dataset for training and testing respectively
2. put training data and testing data in .mat format in corresponding folders
3. run creat_pathlist.py to create *.txt ,for example './pathlist/datalist_NSSR_P.txt'
4. By the way , you can change the Data reading method by changing ./*/clean_dataset.py

train

Run ./sf_8_CAVE/train.py

test

Run ./sf_8_CAVE/tst.py

Contact

Weisheng Dong, Email: wsdong@mail.xidian.edu.cn
Chen Zhou, Email: zhouchen_7@163.com