DN-ResNet: Efficient Deep Residual Network for Image Denoising

@article{Ren2018DNResNetED,
  title={DN-ResNet: Efficient Deep Residual Network for Image Denoising},
  author={Haoyu Ren and Mostafa El-Khamy and Jungwon Lee},
  journal={ArXiv},
  year={2018},
  volume={abs/1810.06766}
}
A deep learning approach to blind denoising of images without complete knowledge of the noise statistics is considered. [] Key Method An edge-aware loss function is further utilized in training DN-ResNet, so that the denoising results have better perceptive quality compared to conventional loss function. Next, we introduce the depthwise separable DN-ResNet (DS-DN-ResNet) utilizing the proposed Depthwise Seperable ResBlock (DS-ResBlock) instead of standard ResBlock, which has much less computational cost.
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