Denoising image of single precision & many pixels using Deep learning
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I'd like to denoise a single precision image using Deep learning, which is a provided as "DnCNN" and "denoiseImage".
Noise follows typical Gaussian, and my original image size is about 2000 x 2000, and tif version.
To train the network with my data, I use "imageDatastore and denoisingImageDatastore" as shown in https://www.mathworks.com/help/images/train-and-apply-denoising-neural-networks.html.
- I think I need to use "augmentedImageDatastore" due to my image size over 256 x 256, but it seems impossible using it with "denoisingImageDatastore". Is it right? or there is other way to use them together?
- Another I wonder is... the single precision image should be scaled by 10e-6 to put Gaussian nosie using "imnoise", and I think there is no ways to do that when using "denoisingImageDatastore". Is also right?
Thanks for your help.
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yanqi liu
2022-2-15
yes,sir,may be use denoisingImageDatastore to make data
during process,the data may be normalized before train
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