This is the code of the paper "Attention-Based Octave Network for Hyperspectral Image Denoising" This network is implemented in Pytorch
1.dataset
Please download the open dataset The Washington DC Mall(DC) from https://engineering.purdue.edu/~biehl/MultiSpec/hyperspectral.html
The Indian Pines dataset from https://engineering.purdue.edu/~biehl/MultiSpec/hyperspectral.html
The Pavia University dataset from http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes#Pavia_University_scene
2.get started
Please run "aug.py" and "complex_noise_dataset_aug.py" to generate training set and test set.
3.train and test
please run "train.py" to train the model and run "test.py" to evaluate it.