In this project, I developed the Multi-level Rotation Haar wavelet Convolutional Neural Network for image deblurring. It is implemented by Keras.
- tensorflow 2.3.1
- numpy 1.18.1
- keras 2.4.3
Download DIV2K_train_LR_x8 and DIV2K_valid_LR_x8 from https://data.vision.ee.ethz.ch/cvl/DIV2K/
Move them to the folder DIV2K.
Run the following code for training and test:
python3 init.py -tr DIV2K/DIV2K_train_HR/ -t DIV2K/DIV2K_valid_HR/ -a wavelet -m train
python3 init.py -t DIV2K/DIV2K_valid_HR/ -a wavelet -m test -lw weights/DenoisingWavelet.h5
Liu P, Zhang H, Lian W, et al. Multi-level wavelet convolutional neural networks[J]. IEEE Access, 2019, 7: 74973-74985.(https://ieeexplore.ieee.org/abstract/document/8732332)
Keras implementation of MWCNN (https://github.com/AureliePeng/Keras-WaveletTransform)