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cszn authored Aug 13, 2018
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Expand Up @@ -71,11 +71,13 @@ FDnCNN can handle noise level range of [0, 75] via a single model.

**Visual Results**

The left is the noisy image corrupted by AWGN, the right is the denoised image by DnCNN.
The left is the noisy image corrupted by AWGN, the middle is the denoised image by DnCNN, the right is the ground-truth.

<img src="figs/05_noisy.png" width="367px"/> <img src="figs/05_dncnn.png" width="367px"/>
<img src="figs/05_25_noisy.png" width="270px"/> <img src="figs/05_25.png" width="270px"/> <img src="testsets/Set12/05.png" width="270px"/>

<img src="figs/102061_noisy.png" width="367px"/> <img src="figs/102061_dncnn.png" width="367px"/>
<img src="figs/02_25_noisy.png" width="270px"/> <img src="figs/02_25.png" width="270px"/> <img src="testsets/Set12/02.png" width="270px"/>

<img src="figs/102061_noisy.png" width="270px"/> <img src="figs/102061_dncnn.png" width="270px"/> <img src="figs/102061.png" width="270px"/>

## Gaussian Denoising, Single ImageSuper-Resolution and JPEG Image Deblocking via a Single (DnCNN-3) Model

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