We plug the CNN denoisers into the half quadratic splitting (HQS) algorithm to solve the following image restoration tasks:
- Image Deblurring
- Image Inpainting
- Single Image Super-Resolution
- Color Image Demosaicking
No task-specific training is done for the above tasks.
Paper Link: http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhang_Learning_Deep_CNN_CVPR_2017_paper.pdf
Code Link: https://github.com/cszn/IRCNN
@inproceedings{zhang2017learning,
title={Learning Deep CNN Denoiser Prior for Image Restoration},
author={Zhang, Kai and Zuo, Wangmeng and Gu, Shuhang and Zhang, Lei},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
pages={3929--3938},
year={2017},
}
Kai Zhang (2021). Learning Deep CNN Denoiser Prior for Image Restoration (https://github.com/cszn/IRCNN), GitHub. Retrieved .
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PyTorch version: https://github.com/cszn/DPIR
Is there any one that does not rely on third-party matconv?
See https://github.com/vlfeat/matconvnet/tree/master/examples
hi sir i need to use cnn (deep neural network) in classification of binary images
please
could you help me