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Topic: Can multiple resampling operations always be lossless? (Read 16785 times) previous topic - next topic
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Can multiple resampling operations always be lossless?

Reply #25 –
Quote from: hellokeith on
When doing editing inside of Audition on a 44.1/16 wav, does the edit operation (adding an effect for example) do any kind of internal upsampling such that the edit is higher precision and then downsampled when finalized? Or do I need to upsample the entire wav first?


It won't change the sampling rate, but it will work at higher numerical precision (i.e. bit depth) internally and dither back to 16-bit afterwards.

There's no need to change sampling rate, but working at higher bit-depth (or floating point) until you finalise the edit will be beneficial in reducing the accumulation of noise. Working in floating point also eliminates the danger of clipping distortion until you finally dither down to 16-bit after editing.
Dynamic – the artist formerly known as DickD

Can multiple resampling operations always be lossless?

Reply #26 –
Quote from: AndyH-ha on
When CoolEdit/Audition  (and at least some other programs) resample, say from 44.1kHz to 88.2kHz, we end up with twice as many samples. Each sample is a number. None of the numbers in that twice as many samples is the same as any of the numbers in the original samples. The program has not simply interpolated new values between the existing values, it has calculated the value for every sample of the result.
If it does do that, then it's a little odd. As far as I can see, integer upsampling can be performed optimally without changing the original samples. Remember, though, that this isn't linear (trend line) type interpolation - this is bandlimited interpolation.

Can multiple resampling operations always be lossless?

Reply #27 –
I’m not explaining or defending, just pointing out what I see. If the original sample values are lost, because of whatever reason, then there is no mapping back to them with these kinds of calculations, no?

Can multiple resampling operations always be lossless?

Reply #28 –
Quote
Considerable research has been devoted to the problem of interpolating discrete points. A comprehensive survey of ``fractional delay filter design'' is provided in [#!LaaksoB!#]. A comparison between classical (e.g., Lagrange) and bandlimited interpolation is given in [#!SchaferAndRabiner!#]. The book Multirate Digital Signal Processing [#!Crochiere!#] provides a comprehensive summary and review of classical signal processing techniques for sampling-rate conversion. In these techniques, the signal is first interpolated by an integer factor $L$ and then decimated by an integer factor $M$. This provides sampling-rate conversion by any rational factor $L/M$. The conversion requires a digital lowpass filter whose cutoff frequency depends on $\max\{L,M\}$. While sufficiently general, this formulation is less convenient when it is desired to resample the signal at arbitrary times or change the sampling-rate conversion factor smoothly over time.


The bandlimited interpolation algorithm offered in that paper seems to be geared towards a hardware implementation.  I wonder if it still holds merit with the growth of software-based systems?

Also, can someone provide real-world examples of the two scenarios mentioned (which I bolded)?

Can multiple resampling operations always be lossless?

Reply #29 –
Quote from: AndyH-ha on
I’m not explaining or defending, just pointing out what I see. If the original sample values are lost, because of whatever reason, then there is no mapping back to them with these kinds of calculations, no?
Fair enough, sorry for the pointless argument.

Quote from: hellokeith on
The bandlimited interpolation algorithm offered in that paper seems to be geared towards a hardware implementation.  I wonder if it still holds merit with the growth of software-based systems?

Also, can someone provide real-world examples of the two scenarios mentioned (which I bolded)?

Actually, I can - but not from the audio world. My research work is on the simulation of radar/sonar return signals. One of the important phenomena in radar is the Doppler shift - this is the frequency (or phase which is equivalent) shift caused by scattering of the radar signal by targets moving relative to the receiver or transmitter. As the Doppler shift can change on the order of the length of the signal (especially for continuous wave (CW) systems), the simulator needs to be able to apply time-dependent "warping" on the phase and frequency of the signal. We use a similar method to simulate the effects of local-oscillator phase noise on the received signal.

In audio, this same approach could be used to simulated Doppler in a game's audio processor, or simulate the effects of time dependent phase and frequency shifts on a signal (imagine simulating a trombone).

Can multiple resampling operations always be lossless?

Reply #30 –
Another application where the change in frequency with time is significant is SETI, the search for extraterrestrial intelligence. In analyzing the data looking for a coherent signal, one of the factors which is taken into account is that a signal source may be in orbit around a planet. This would result in "chirping". The SETI  at home application applies varying degrees of skew to the data in order to cancel this effect.

Can multiple resampling operations always be lossless?

Reply #31 –
Quote from: hellokeith on
Quote
The conversion requires a digital lowpass filter whose cutoff frequency depends on $\max\{L,M\}$. While sufficiently general, this formulation is less convenient when it is desired to resample the signal at arbitrary times or change the sampling-rate conversion factor smoothly over time.


Also, can someone provide real-world examples of the two scenarios mentioned (which I bolded)?


Sample playback synthesis (commonly knows as "samplers") such as the E-mu Emulator or Akai S1000