Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

@article{Zhang2016BeyondAG,
  title={Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising},
  author={K. Zhang and Wangmeng Zuo and Yunjin Chen and Deyu Meng and Lei Zhang},
  journal={IEEE Transactions on Image Processing},
  year={2016},
  volume={26},
  pages={3142-3155}
}
  • K. ZhangW. Zuo Lei Zhang
  • Published 13 August 2016
  • Computer Science
  • IEEE Transactions on Image Processing
The discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance. [] Key Method With the residual learning strategy, DnCNN implicitly removes the latent clean image in the hidden layers. This property motivates us to train a single DnCNN model to tackle with several general image denoising tasks, such as Gaussian denoising, single image super-resolution, and JPEG image deblocking. Our extensive experiments demonstrate that…

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