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To be fair, the terms in literature are all over the place. image space and spectral space is what I read most often (not necessarily in English). I personally
by raxxorrax 6y ago
To be fair, the terms in literature are all over the place. image space and spectral space is what I read most often (not necessarily in English). I personally would prefer just source and target space, especially since we have imaging as an application.
I think the explanation was quite good, but I implemented a DCT once as a student (with shitty code and slow as hell, don't roll your own matrix multiplication). The Wikipedia article was bad at the time, but it has really good info now.
The topic can take a while to get it. I think looking at the base functions helps a lot. Every image is basically an overlap of these base functions which are each parameterized through an amplitude and phase. I transformed some images with basic shapes with Matlab until it really clicked.
- ajross 6y ago> To be fair, the terms in literature are all over the place. To be actually fair, the title is "EXPLAIN LIKE I'M FIVE" and clearly the intent of the presentation is for users who haven't read The Literature. I mean, look, at an analysis level the DCT requires just a little bit of high school calculus and anyone with even a passing familiarity with this stuff can pick it up from The Literature without problem. No one disputes that, and lots of us learned it like that. But given that, why write this in the first place? Clearly the sense of the author is that people exist who don't have that background but want to understand frequency transforms. Telling those people to "go look it up" is completely missing the point.