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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.

Respuesta aceptada

yanqi liu
yanqi liu el 15 de Feb. de 2022
yes,sir,may be use denoisingImageDatastore to make data
during process,the data may be normalized before train

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