I have written a python script which uses the Noise2Noise: Learning Image Restoration without Clean Data implementation of the Auto Encoder which is useful to remove noise from images. In the original paper implementation they were using full images so there were no border artifacts.
I want to use my script on raw images from long exposures and high ISO to remove the noise. For this purpose, I fragment the image into small fractions which are run through the Auto Encoder network. After prediction, original image is reconstructed. However, the problem is with the border connections between slices (As showed in the images below). Do you have any suggestions what would be the best idea to "fix" it? I would be more than grateful!