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by kens 678 days ago
I'm surprised that the article doesn't mention Fourier transforms and neither do any of the comments. All the talk about aliasing and different filters makes a whole lot more sense if you take a look at the frequency domain. (Unfortunately I don't have time to elaborate here. But Fourier transforms are so useful in many ways that I encourage people to learn more.)
1 comments

If you want to go hardcore into the frequency domain, may I suggest "A Fresh Look at Generalized Sampling" by Nehab and Hoppe[1]. That said, while a frequency-centric approach works super well for audio, for images you need to keep good track of what happens in the spatial domain, and in particular the support of sampling filters needs to be small.

[1]: https://hhoppe.com/filtering.pdf