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this post was submitted on 28 May 2024
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I can try to explain, but there are people who know much more about this stuff than I do, so hopefully someone more knowledgeable steps in to check my work.
What does ‘random’ or ‘noise’ mean? In this context, random means that any given bit of information is equally as likely to be a 1 or a 0. Noise means a collection of information that is either random or unimportant/non-useful.
So, you say “Compression saves on redundant data”. Well, if we think that through, and consider the definitions I’ve given above, we will reason that ‘random noise’ either doesn’t have redundant information (due to the randomness), or that much of the information is not useful (due to its characteristic as noise).
I think that’s what the person is describing. Does that help?
I agree with your point, but you're arguing that noise can be redundant data. I am arguing that redundant data is not necessarily noise.
In other words, a signal can never be filtered losslessly. You can slap a low pass filter in front of the signal and call it a day, but there's loss, and if lossless is a hard requirement then there's absolutely nothing you can do but work on compressing redundant data through e.g. patterns, interpolation, what have you (I don't know much about compression algos).
A perfectly noise free signal is arguably easier to compress actually as the signal is more predictable.