This is TNLRD-ACMMM-Reproductive for MM'17 'Learning Non-local Image Diffusion for Image Denoising' ----FoETrainingSets180: training images ----testCodes: contains test codes for experiments described in [1]. Run test68tnlrd.m ----trainingCodes: contains training codes for experiments described in [1]. --------TNLRD-plain: greedy training + joint training, the parameters are initialized randomly. ------------greedy : greedy training, run GreedyTraining.m ------------joint : joint training, run JointTraining.m --------TNLRD-tnrd : joint training using the parameters in TNRD [2] models. Run JointTraining.m --------TNLRD-ssim : training with ssim-like loss instead of l2 loss. Run JointTrainingwithSSIM.m [1] Peng Qiao, Yong Dou, Wensen Feng, Rongchun Li, and Yunjin Chen. 2017. Learning Non-local Image Diffusion for Image Denoising. In ACM Multimedia. 1847–1855. [2] Yunjin Chen, Wei Yu, and Thomas Pock. 2015. On learning optimized reaction diffusion processes for effective image restoration. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 5261–5269. If you use this code, please cite our paper: @inproceedings{qiao2017learning, title={Learning Non-local Image Diffusion for Image Denoising}, author={Qiao, Peng and Dou, Yong and Feng, Wensen and Rongchun Li and Chen, Yunjin}, booktitle={ACM Multimedia}, pages={1847-1855}, year={2017}, }
qiaopTDUN/TNLRD-ACMMM-Reproductive
TNLRD-ACMMM-Reproductive for MM'17 'Learning Non-local Image Diffusion for Image Denoising'
MATLAB