I'm trying to train a deep nerual network that takes in input, an signal in the frequency domain, and attempts to learn a mapping to another signal in the frequency domain.
Basically, the input to the network is a 2d matrix with separate real and imaginary components with shape (256, 256, 2). Taking the IFFT of this input, produces the right image.
The input image in(after IFFT operation on the signal) looks like this:
My question is this: What could be causing the output to appear this way? I looked at image scaling issues that could potentially lead to this, the image shown is adjusted with log scaling. The fact that there are two "lines" (vertical and horizontal) leads me to think that it might have to do with the IFFT "erasing" a lot of the information. My apologies for the wording of the title, couldn't figure out how to describe this issue.