These are the same thing. A shape with a solid boundary is a a signal with a discontinuous step: If you Fourier it, it has infinite nonzero terms, therefore you can't represent it exactly with any finite amount of frequencies, and therefore a finite amount of samples.
In the case of Moiré patterns in pictures, we have lines in the real world that need to fit into pixels that fit a larger area than the Nyquist rate of those lines. The Moiré effect in pictures is just the interference pattern caused by this aliasing.
If you look at just a column of the image, and imagine the signal as being the brightness varying over the Y coordinates, you can imagine the mortar being an occasional regular pulse, and when your sampling rate (the pixel density) isn't enough, you get aliasing: you skip over, or overrepresent, the mortar to brick ratio, variably along the signal.
Now if you look at the graph in that picture, doesn't that look awfully similar to what happens if you try to sample an audio file at an inferior rate for display purposes?
In fact, try it right now, download Audacity, go to Generate>Tone, click OK with whatever settings it's fine, press Shift+Z to go down to sample level zoom, then start zooming out. Eventually, you'll see some interesting patterns, which are exactly the sort of aliasing caused by resampling I'm talking about:
How do we add more colours (besides just picking a random colour, which wouldn't be helpful)?
By sampling the signal more often ("multi-sample anti aliasing"), also known as increasing the resampling rate, then representing that with a wider bit depth (not just 1 bit "yes/no", but multiple bits forming a color/opacity), since we do have more than 1 bit per pixel that can be used already.
I'll give it to you that this is "anti aliasing", not "not having aliasing in the first place", but the Fourier argument above is the reason why in computer graphics we practically always have to "settle for" AA instead.
In the case of Moiré patterns in pictures, we have lines in the real world that need to fit into pixels that fit a larger area than the Nyquist rate of those lines. The Moiré effect in pictures is just the interference pattern caused by this aliasing.
If you look at just a column of the image, and imagine the signal as being the brightness varying over the Y coordinates, you can imagine the mortar being an occasional regular pulse, and when your sampling rate (the pixel density) isn't enough, you get aliasing: you skip over, or overrepresent, the mortar to brick ratio, variably along the signal.
https://imgur.com/a/BiZcxG5
Now if you look at the graph in that picture, doesn't that look awfully similar to what happens if you try to sample an audio file at an inferior rate for display purposes?
In fact, try it right now, download Audacity, go to Generate>Tone, click OK with whatever settings it's fine, press Shift+Z to go down to sample level zoom, then start zooming out. Eventually, you'll see some interesting patterns, which are exactly the sort of aliasing caused by resampling I'm talking about:
https://i.imgur.com/bX2IFp8.png