If you're doing this then you assume your signal is stationary in the window length. Many times, it's not...
Why is it a bad idea to filter by zeroing out FFT bins? (2020)
11–20 of 43 posts
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#12I disagree that it's always a bad idea. If you didn't have real data in those bins to begin with, then the absence of ringing was never real either. You're just choosing between interpolation strategies to fill in the data you deleted. You have to realize that whatever you do, you're making up data. One could say that you're taking out your dry erase marker and writing in your priors. For image processing, you probab…
> If you didn't have real data in those bins to begin with, then the absence of ringing was never real either.
What is unreal data? If you have periodic data that's not aligned you're going to have a continuous signal going all the way to the high frequencies.
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#13I disagree that it's always a bad idea. If you didn't have real data in those bins to begin with, then the absence of ringing was never real either. You're just choosing between interpolation strategies to fill in the data you deleted. You have to realize that whatever you do, you're making up data. One could say that you're taking out your dry erase marker and writing in your priors. For image processing, you probab…
> If you didn't have real data in those bins to begin with, then the absence of ringing was never real either. What is unreal data? If you have periodic data that's not aligned you're going to have a continuous signal going all the way to the high frequencies.
>What is unreal data?
The easiest example would be when an earlier step supersampled the data, and you know that nothing above the original Nyqiust could possibly reflect reality. That's one example of when you'd want to zero bins.
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#14Earlier quoted context omitted.
> If you didn't have real data in those bins to begin with, then the absence of ringing was never real either. What is unreal data? If you have periodic data that's not aligned you're going to have a continuous signal going all the way to the high frequencies.
> What is unreal data? The easiest example would be when an earlier step supersampled the data, and you know that nothing above the original Nyqiust could possibly reflect reality. That's one example of when you'd want to zero bins.
Yes, but what's stopping you from using non brick wall windows and filtering nyquist frequencies before sampling? Situations where "unreal" data is present only in higher frequencies is rare, and situations where all data is absent from the higher frequencies are very rare unless you sample in a perfect context where everything is aligned with the sampling period.
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#15This would be a really good interview question!
I think it's a terrible interview question, unless maybe you're hiring an electrical engineer. It's not something you can expect someone to reason through from the basics, and it's not something I'd expect someone to know unless they've worked on problems involving the technique.
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Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#16This is indeed an excellent way of filtering if your audio is cyclic and fits into a single FFT, like a periodic waveform, a drum loop or an Optigan track. Just make sure not to apply any window.
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#17Why use an FFT at all? Yes it's easy but you'll almost always get a better result with a lot less computation by building an actual digital filter.
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#18A much less well known fact about the FFT (or the DFT) is that it is also exhibits a brickwall (rectangular) response. This can manifest itself when using zero padding in the frequency domain for upsampling, but is also the reason for artifacts when FFTing a nonperiodic window.
It's used in OFDM, where the subchannels are generated by an FFT and have a sinc shape (the Impulse response of the FFT) in the frequency domain.
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#19as mentioned, worth pointing out that most practical digital filters don't have that many taps so unless you have other reasons to go to the frequency domain, time domain filtering can be faster...
but yeah, the implicit boxcar is a sinc.
sometimes it's used for image data as 2d convolutions can be expensive though...
Re: Why is it a bad idea to filter by zeroing out FFT bins? (2020)
#20Why use an FFT at all? Yes it's easy but you'll almost always get a better result with a lot less computation by building an actual digital filter.
Applying a FIR in frequency domain faster for 1D filters longer than some very small number, usually 7-16. The old school graphics and audio filters are shorter sure, but they are also horribly bad compared to what you can do with a designed filter in the 20-40 range.