strange results with out-of-sample prediction about n2v HOT 1 CLOSED

Hi Ben,

after having a look at your data, multiple things need to be pointed out.

Anyways: here my main points for you:

1. None of your images are particularly noisy.
2. If they would be, I would strongly suggest NOT to train the RGB example (you have microscopy images, to RGB images... you even have single channel images!)
3. The second image you have is, as you say, out of focus. This is not the same as being in-focus but noisy, you see?
4. Even if you data would be subject to large amounts of pixel independent noise (this is what Noise2Void can address, as the paper states), the second image is not as the first. I have included some histograms for you to see that the data lives in entirely different intensity ranges. This alone would cause problems, even if all the rest would be fine.

I hope this helps a bit and maybe motivate you to have a look into our papers again. I'm sure N2V could be helpful for you, but you will need to train on images that are subject to pixel independent noises (e.g. shot noise) and then apply either to the same image or images that are similar in nature, not just some other images coming from the same microscope.

Best,
Florian

from n2v.