Double nitpick, according to Wikipedia, your definition is a "minority usage". I teach signal Processing and hadn't heard of that one, so thanks for pointing me to it!

Nyquist as half sampling rate is what I use

https://en.m.wikipedia.org/wiki/Nyquist_frequency#Other_meanings

I'll add that frequencies above the Nyquist point fold into lower frequencies. So you need to filter out the higher frequencies with a low pass filter.

This isn't just for audio but any type of sampling frequencies. For example in video when you see wagon wheels going backwards, helicopter blades moving slowly, or old CRT displays where there is a big bright horizontal line sweeping. That's all frequency folding around half the frame rate.

It also applies to grids in images. The pixels in a display act a sample points and you get frequency folding leading to jagged lines. Because a line segment is a half cycle of a square wave with a period of twice the length.

When that segment is diagonal it become a two dimensional signal with even higher frequency components in each axes. This leads to jagged diagonal lines. This is called aliasing as the higher frequencies have an alies as lower frequencies.

So when you apply antialiasing in video games it's doing math to smear the signal along the two axis of the display. This makes a cleaner looking line.

Thanks! Your nitpicking is most welcome.

Little nitpick to you:

Nyquist will ensure that you preserve artifacts that indicate primary frequency(ies) of interest, but you'll lose nuance for signal analysis.

When we're analyzing a signal more deeply we tend to use something like 40x expected max signal frequency, it'll give you a much better look at the signal of interest.

This is because your signal of interest, unless purely sinusoidal, has higher frequency features such as harmonics, so if you sample at Nyquist you'd lose all of that. Nyquist theorem still stands, it's just you wanna look at higher frequency than you realize because you wanna see higher frequency components of your signal.

Thanks, I agree, it’s one of my favorite shots from this camera.

The fighter of the Nyquist.

Thanks! I’d love to hear your thoughts if you feel like sharing.

I don't have the time to write a well thought out reply, but CDs trump cassettes in terms of both dynamic range and noise floor. Records are worse than cassettes in both categories. I would personally trade a small amount of frequency response for the other two.

That said, people are... well people. Do what makes you happy.

Of course there’s some ancient broadcast standard at the bottom of 44.1khz, thanks for the clarification! (I work in film/TV and still struggle with explaining explaining ‘illegal’ values to some clients on certain deliverables)

As for busy road at night, I’m afraid that with this way of doing scanning photography it would be quite uninteresting. The motion is way too quick, and cars would render as with either weird vertical lines or very small diagonal squiggles, depending on which direction you scan.

I suggest looking up some talks by the Italian photographer Adam Magyar, he’s done some great talks on transchronologal (?) photography, and is a great artist himself.

I haven’t really considered that, I’m assuming the (in this case) vertical sampling is ‘global’, as in the values at each sensor site is locked at the same time and then read out from the serial bus.

If there was a delay, stuff like fluorescent lighting would read as a moire pattern, but I’ve only ever encountered streaking/linear distortion in those circumstances.

I think the ‘griddyness’ or general sense of direction in the water is purely a function of how water moves and not a result of readout delay.

I’d love to be proven wrong, though, so if I can do some experiment to determine either way, I’m all ears.

It comes from mathematical interpolation. In order to find the frequency of a sine curve (and all signals are combinations of sine curves) you need at least two measured points per period. So the measurement frequency needs to be at least twice the signal frequency - at least of the parts of the signal you want to preserve. Frequencies higher than 22kHz are useless to our ears, so we can ignore them when sampling.

https://en.m.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem

Agreed, it’s usually not that spiky