It may sound like marketing wank, but it does a appear to be an established term of art in academia as far back as 1997 [1]
It just means that a person can't readily distinguish between the compressed image and
the uncompressed image. Usually because it takes some aspect(s) of the human visual system into account.
I read “perceptually lossless” to be equivalent to “transparent”, a more common phrase used in the audio/video codec world. It’s the bitrate/quality at which some large fraction of human viewers can’t distinguish a losslessly-encoded sample and the lossy-encoded sample, for some large fraction of content (constants vary in research papers).
As an example, crf=18 in libx264 is considered “perceptually lossless” for most video content.
Can you propose a better term for the concept then? Perceiving something as lossless is a real world metric that has a proper use case. "Perceptually lossless" does not try to imply that it is not lossy.
I work in graphics. Calling this transparency would be a terrible idea and make a lot of discussions around compression of videos and images with actual transparency very confusing.
Does the compression algorithm work well for transparency? Yes, it's effect on transparency is totally transparent! In fact the transparency is fully transparently compressed by our codec.
Yeah, don't do this please. Perceptually lossless is a term I've heard lots of times before and companies developing codecs usually have a fairly strong technical basis for making the claim. As in, it's not like they just glance at the results and say "yep, looks good to me". Rather, they'll be looking and spectral curves and image diffs - probably also motion diffs for videos - and checking whether they the losses are small enough to be undetectable to human eyes.
why not? if you change one pixel by one pixel brightness unit it is perceptually the same.
for the record, I found liveportrait to be well within the uncanny valley. it looks great for ai generated avatars, but the difference is very perceptually noticeable on familiar faces. still it's great.
For one, it doesn't obey the transitive property like a truly lossless process should: unless it settles into a fixed point, a perceptually lossless copy of a copy of a copy, etc., will eventually become perceptually different. E.g., screenshot-of-screenshot chains, each of which visually resembles the previous one, but which altogether make the original content unreadable.
Perceptual closure under repeated iterations is just a stronger form of perceptual losslessness, then, after k generations instead of the usual k=1. What you’re describing is called generation loss, and there are in fact perceptually lossy image codecs that have essentially no generation loss; jpeg xl is one https://m.youtube.com/watch?v=FtSWpw7zNkI
There is "Is identical", "looks identical" and "has lost sufficient detail to clearly not be the original." - being able to differentiate between these three states is useful.
Importantly the first one is parameterless, but the second and third are parameterized by the audience. For example humans don't see colour very well, some animals have much better colour gamut, while some can't distinguish colour at all.
Calling one of them "perceptually lossless" is cheating, to the disadvantage of algorithms that honestly advertise themselves as lossy while still achieving "looks identical" compression.
It's a well established term, though. It's been used in academic works for a long time (since at least 1970), and it's basically another term for the notion of "transparency" as it relates to data compression.
I honestly don't notice this anymore. Advertisers have been using such language since time immemorial, to the point it's pretty much a rule that an adjective with a qualifier means "not actually ${adjective}, but kind of like it in ${specific circumstances}". So "perceptually lossless" just means "not actually lossless, except you couldn't tell it from truly lossless just by looking".
It is in no way the definition of lossy. It is a subset of lossy. Most lossy image/video compression has visible artifacting, putting it outside the subset.
It means what it already says for itself, and does not need correcting into incorrectness.
"no perceived loss" is a perfectly internally consistent and sensible concept and is actually orthogonal to whether it's actually lossless or lossy.
For instance an actually lossless block of data could be perceptually lossy if displayed the wrong way.
In fact, even actual lossless data is always actually lossy, and only ever "perceptually lossless", and there is no such thing as actually lossless, because anything digital is always only a lossy approximation of anything analog. There is loss both at the ADC and at the DAC stage.
If you want to criticize a term for being nonsense misleading dishonest bullshit, then I guess "lossless" is that term, since it never existed and never can exist.
Similar to your points, i also expect `perceptually lossless` to be a valid term in the future with respect to AI. Ie i can imagine a compression which destroys detail, but on the opposite end it uses "AI" to reconstruct detail. Of course though, the AI is hallucinating the detail, so objectively it is lossy but perceptibly it is lossless because you cannot know which detail is incorrect if the ML is doing a good job.
In that scenario it certainly would not be `transparent` ie visually without any lossy artifacts. But your perception of it would look lossless.
Why don't you think it's a thing? A trivial example is audio. A ton of audio speakers can produce frequencies people cannot hear. If you have an unprocessed audio recording from a high end microphone one of the first compressions things you can do is clip of imperceptible frequencies. A form of compression.
As there are several patents, published studies, IEEE papers and thousands of google results for the term, I think it's safe to say that many people do not agree with your interpretation of the term.
"As a rule, strong feelings about issues do not emerge from deep understanding." -Sloman and Fernbach
It is definitely a thing given a good perceptual metric. The metric even doesn't have to be very accurate if the distortion is highly bounded, like only altering the lowermost bit. It is unfortunate that most commonly used distortion metrics like PSNR are not really that, though.
But that's mathematically impossible, to restore signal from extremely low bitrate stream with any highly bounded distortion. Perhaps only if you have highly restricted set of posible input, which online meetings aren't.
> Perhaps only if you have highly restricted set of posible input, which online meetings aren't.
Are you sure? After all, you can effectively summarize meetings in a plain text which is extremely restricted in comparison to the original input. Guaranteed, exact manner of speech and motions and all subtleties should be also included to be fair, but that information is still far limited to fill the 20 kbps bandwidth.
We need far more bandwidth only because we don't yet have an efficient way to reconstruct the input faithfully from such highly condensed information. Whenever we actually could, we ended up having a very efficient lossy algorithm that still preserves enough information for us human. Unless you are strictly talking about the lossless compression---which is however very irrelevant in this particular topic---, we should expect much more compression in the future even though that might not be feasible today.
Ability to tell MP3 from the original source was always dependent on encoder quality, bitrate, and the source material. In the mid 2000's, I tried to encode all of my music as MP3. Most of it sounded just fine because pop/rock/alt/etc are busy and "noisy" by design. But some songs (particularly with few instruments, high dynamic range, and female vocals) were just awful no matter how high I cranked the bitrate. And I'm not even an "audiophile," whatever that means these days.
No doubt encoders and the codecs themselves have improved vastly since then. It would be interesting to see if I could tell the difference in a double-blind test today.
I find generic ABX tests not great, personally, because I generally don’t know what to be listening for. However, with songs I’ve listened to lossless my whole life, it’s much easier to spot encoding failures - an intuitive “wait, that cymbal crash sounded different” or “that multi-instrument harmonic should be cleaner/dirtier.”
That being said, 320Kbps AAC encoded by Core Audio I’ve found to be pretty much transparent with anything I’ve thrown at it. Anything less than that (256Kbps AAC, 320Kbps MP3, etc) I can ABX sometimes, as long as I’m familiar with the source material, and usually only with quality headphones. Although no streaming services provide that, so I’m stuck with ALAC through Apple Music for streaming (which is more convenient than my old solution, which was transcoding and transferring to an iPod ~20k songs selected from ~90k in my library based on a variety of rules than never gave me the song I’m looking for). And really, ~900Kbps lossless is pretty easy to justify these days with 5G data speeds and generally much higher data transfer limits.
The other downside to storing losing encodings these days is the fact that almost everyone uses Bluetooth for their listening, which is an additional lossy encoding. While 256Kbps AAC/320Kbps MP3 might be transparent in some cases, when it’s re-encoded it very rarely is (in my experience)
iirc there's "easy" (though i don't know them) tests to validate if the signal is lossless or not. When played over speakers for humans, at least.
I always intend to figure out how that works, because i don't feel a lot of audiophiles are actually speaking truth in many cases lol. Still, i don't know - i can't remember my sources to figure it out for myself :/
Lossy audio formats suddenly become very discernible once you subtract the left channel from the right channel. Try that with Lossless audio vs MP3, Vorbis, Opus, AAC, etc. You're listening to only the errors at that point.
A family member of mine didn't see the point of 1080p.
Turned out they needed cataract surgery and got fancy replacement lenses in their eyes.
After that, they saw the point.
Needing to define "perception" is a much weaker criticism than "isn't a thing and doesn't make sense".
It's easy enough to specify an average person looking very closely, or a 99th percentile person, or something like that, and show the statistics backing it up.
It just means that a person can't readily distinguish between the compressed image and the uncompressed image. Usually because it takes some aspect(s) of the human visual system into account.
[1] https://scholar.google.com/scholar?hl=en&as_sdt=0%2C22&q=per...