You don't control the resolution in modern cameras, it is set by the system, and as resolution is set in the output media the "appearance" is limited to zoom, especially with modern printers who's algorithms do a far better job of interpolation than anything a user can achieve.
Ahh, I really shouldn't get involved in these in depth discussions as often ideas are summarily dismissed...
Thanks to Arvo for providing the answer already :-)
While such transformations into the frequency domain are mathematical, an appreciation of how they look in the frequency domain, and how different response functions and signals combine, can help one understand the total system response and the final result.
There are also many practical uses of using FFT, DFT,...
Yes, for looking at texture, I use the GIMP Threshold function set to 0.5 on the magnitude plot out of G'MIC's FFT.
I use the Threshold function so that all frequencies over 50% "power" come out pure white as can be seen above, especially useful to me for comparisons. This plot tell me that "MTF50" is sort of occurring around 0.2cy/px because the edges of the plot represent Nyquist, and the original image was taken in 2x2 binned mode on-sensor, i.e. 10 um pixels.
So if I have a camera with a sensor pixel pitch of 5 um then that is a spatial frequency of 100 lp/mm. A 100 ppi monitor has a spatial frequency of about 100/25/2 = 2 lp/mm per the above chart, in other words a magnification factor of about 50.
I have a vague memory from prior work as an Electrical Engineer. Convert the polar FFT to Cartesian co-ordinates. Multiply the rectangular values. Convert the result back to polar and apply the inverse transformation?