Modifying denoising image datastore to generate different types of noise

Hi,

I'm trying to understand / edit the code for the function denoisingimagedatastore to generate other types of noise besides Gaussian noise. I'm looking to introduce spekle noise to the pristene images.

Please let me know if you have any thoughts on how to do this, thanks!

Answer 1

[Johanna Pingel]

Try following this example:

https://www.mathworks.com/help/images/single-image-super-resolution-using-deep-learning.html while this doesn't do exactly what you're looking for, you want to set up a

randomPatchExtractionDatastore

As input to your network. Put your input images and your output images to the network in two imagedatastores, and then use randomPatchExtractionDatastore(imdsIN,imdsOUT,patchSize)

This example helped me figure out how to customize an image-to-image network like you're trying to do. Let me know when you get results!

[Jonathan Foo]

Thanks for your answer, I'll check it out!