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> We do [cubic curve fitting] all the time in image processing, and it works very well. It would probably work well for audio as well, although it's not used --

> We do [cubic curve fitting] all the time in image processing, and it works very well. It would probably work well for audio as well, although it's not used -- not in the same form, anyway -- in these applications. Is there a reason the solution that "works very well" for images isn't/can't be applied to audio?

amlib 9mo ago
AFAIK it introduces harmonic distortion
- pixelpoet 9mo ago
  I'd love to know more about this, do you perhaps have any refs? Thanks
  - amlib 9mo ago
    Not an expert in this field, just a scrub, so I can't really give you much. There is this website that has painstakingly compares many resampling algorithms from all sorts of software: https://src.infinitewave.ca https://src.infinitewave.ca Try it's mirror if you can't access it: https://megapro17.github.io/src/index.html https://megapro17.github.io/src/index.html The only one that says it is a cubic interpolation is the "Renoise 2.8.0 (cubic)" one, the spectrogram isn't very promising with all sorts of noise, intermodulation and aliasing issues. And, by switching to the 1khz tone spectrum view you can see some harmonics creeping up. When I used to mess with trackers I would sometimes chose different interpolations and bicubic definitely still colored the sound, with sometimes enjoyable results. Obviously you don't want that as a general resampler...
    - butterknife 9mo ago
      Just to note that this site hasn't been updated for a while. Much better, more modern and with automated upload analysis site would be [1] although it is designed for finding the highest fidelity resampler rather than AB comparisons. [1] https://src.hydrogenaudio.org https://src.hydrogenaudio.org
adgjlsfhk1 9mo ago
The short answer is that our eyes and ears use very different processing mechanisms. Our eyes sense using rods and cones where the distribution of them reflects a spatial distribution of the image. Our ears instead work by performing an analogue forier transform and hearing the frequencies. If you take an image and add lots of very high frequency noise, the result will be almost indistinguishable, but if you do the same for audio it will sound like a complete mess.

amlib 9mo ago

AFAIK it introduces harmonic distortion

pixelpoet 9mo ago
I'd love to know more about this, do you perhaps have any refs? Thanks
- amlib 9mo ago
  Not an expert in this field, just a scrub, so I can't really give you much. There is this website that has painstakingly compares many resampling algorithms from all sorts of software: https://src.infinitewave.ca https://src.infinitewave.ca Try it's mirror if you can't access it: https://megapro17.github.io/src/index.html https://megapro17.github.io/src/index.html The only one that says it is a cubic interpolation is the "Renoise 2.8.0 (cubic)" one, the spectrogram isn't very promising with all sorts of noise, intermodulation and aliasing issues. And, by switching to the 1khz tone spectrum view you can see some harmonics creeping up. When I used to mess with trackers I would sometimes chose different interpolations and bicubic definitely still colored the sound, with sometimes enjoyable results. Obviously you don't want that as a general resampler...
  - butterknife 9mo ago
    Just to note that this site hasn't been updated for a while. Much better, more modern and with automated upload analysis site would be [1] although it is designed for finding the highest fidelity resampler rather than AB comparisons. [1] https://src.hydrogenaudio.org https://src.hydrogenaudio.org

adgjlsfhk1 9mo ago

The short answer is that our eyes and ears use very different processing mechanisms. Our eyes sense using rods and cones where the distribution of them reflects a spatial distribution of the image. Our ears instead work by performing an analogue forier transform and hearing the frequencies. If you take an image and add lots of very high frequency noise, the result will be almost indistinguishable, but if you do the same for audio it will sound like a complete mess.