I really liked the explanation that low frequencies mean it is varying slowly which, in the frequency domain, are values close to the center. Previously I never understood the 2D frequency domain images but by thinking of the image's derivatives, the direction and amount of change in brightness of the pixels, we can visualize how far from the center and in what position the corresponding frequency domain point might be at.
NKJEW
This tradeoff thing reminds me of some cool explanations I've seen of the uncertainty principle - where how having more concentrated "information" about frequency (e.g. velocity) correlates with your spatial stuff (e.g. position) being less concentrated.
I really liked the explanation that low frequencies mean it is varying slowly which, in the frequency domain, are values close to the center. Previously I never understood the 2D frequency domain images but by thinking of the image's derivatives, the direction and amount of change in brightness of the pixels, we can visualize how far from the center and in what position the corresponding frequency domain point might be at.
This tradeoff thing reminds me of some cool explanations I've seen of the uncertainty principle - where how having more concentrated "information" about frequency (e.g. velocity) correlates with your spatial stuff (e.g. position) being less concentrated.