Yup, considering someone first has to (or should) define at what point the data is useful and past a level of noise that isn’t useful data. Between the two statements above, no wonder this discussion goes on and on. It was true in the old scanner days too.
Especially when the answer cannot be represented fully by a single number when comparing very different systems.
The
aesthetic quality of noise is only sort-of related to it's pure mathematical level (as represented by a number like S/N).
In other words these two are not of the same use to a photographer:
- gaussian film-like grain with uniform characteristics and apparent smoothness of tonality going from shadows to quarter tones
- blotchy pastes of color with irregular shape and strange posterized transitions from shadows to quarter tones
Both of those can have the same signal to noise ratio as measured mathematically.
Some of these characteristics comes from the sensors, some from the supporting hardware, some from firmware, some from software.
The aesthetics and math become even less tightly related when you add software noise-reduction into the fray. Software can do wonders to reduce/remove/make-more-pleasant noise which it can profile well. For instance if you've ever done audio recording you'll know that some kinds of noise are very hard to remove/reduce in post (e.g. sporadic voices in the background) while others are very easy to remove/reduce (high pitched squeaking in the background) even when they are the same mathematical volume. Furthermore when software knows the characteristics of the noise a particular device produces it can do a better job of reducing it or making it less aesthetically intrusive.
Anyway I'm rambling now. But the point is a sensor does not make a picture, a photographer does - and the sensor is only a small part of the system the photographer will use. It's not really relevant to compare anything besides the end product. And even then it's really only relevant to compare the end product the way YOU would use it (e.g. what lighting sources, what length exposures, what ISOs, what software, etc).