Reversing spectrum of an audio signal is said to be often used in DSP – i.e. applying a low-pass filter is quite a simple operation, compared to a high-pass. So they shift the specrtum by multiplying each other sample by -1, apply the Low-pass filter and then reverse again.
I am wondering if the same processing technique could be applied to images: reverse frequencies, apply edits/processing, reverse again.
Please advice how can a spectrum of a 2D signal be reversed?
Is it something as simple as each other sample inversion as for a 1D audio signal? I'd prefer some code snippets / visual examples to math equations.
I also wonder if FFT of an image, reversing the frequencies, IFFT, FFT, another reversing, IFFT can be considered lossless to the source image?
Also I discovered to myself that a 2D FT can be parallelized into 1D FT's for vertical and horizontal pixel sets.
My research goal is to find a reversible transform of a source image "S" to another image "T", such as that T carries no visual clues to the content of the original image S. A transformation that is reversible, and also not dependent on precise pixel-to-pixel correspondence. I.e. it should be possible to recover original image S after taking a photo of a printed poster with transformed image T – of course with adequate losses / distortions / color regression. Hypothesis that reversing spectrum of an image would scramble it original content has failed.