Pay attention to just how good WebP is at _lossless_ comparison though!
I've always thought that one as flying under the radar. Most get stuck on WebP not offering tangible enough benefits (or even worse) over MozJPEG encoding, but WebP _lossless_ is absolutely fantastic for performance/speed! PNG or even OptiPNG is far worse. And very well supported online now, and leaving the horrible lossless AVIF in the dust too of course.
Lossless WebP is very good indeed. The main problem is that it is not very future-proof since it only supports 8-bit. For SDR images that's fine, but for HDR this is a fundamental limitation that is about as bad as GIF's limitation to 256 colors.
This limit didn't exist in my first version as well as the 4 GB limit. These were artificially introduced to "match" the properties of lossy WebP. We could have done better there.
Were you involved in creating WebP? If so that's super cool! Why would they want to match webp's lossy compression though? To make it more uniform? And do you know why lossy WebP had such a limitation in the first place? Thank you!
I designed the WebP lossless format, wrote the spec, and implemented the first encoder.
The constraint was in WebP lossy to facilitate exact compatibility with VP8 specification and hoping that it would allow hardware decoding and encoding of WebP images using VP8 hardware.
Hardware encoding and decoding were never used, but the limitation stuck.
There was no serious plan to do hardware lossless, but the constraint was copied for "reducing confusion".
I didn't and don't like it that much as more PNG images couldn't be represented as WebP lossless as a result of that.
Wow, that really sucks. I appreciate the explanation as well as your frustration with it.
My desktop had a mixture of PNG and WebP files solely because of this limitation. I use the past tense because they've now all been converted to JPEG XL lossless.
Another group of incompatibility with PNG was 16 bit coding. I had a plan to add it as simply sending two 8 bit images where the second image containing the 8 least significant bits would be predicted to be the same as the first. That way it would not be perfect, but it would be 100x better than how PNG deals with it. WebP had another plan for layers and tiles that never realized, and as a consequence WebP is stuck at 8 bits.
Ah, I didn't know this and I agree this is a fairly big issue and increasingly so over time. I think smartphones in particular hastened the demand for HDR quite a bit, what was once a premium/enthusiast feature you only had to explicitly buy into.
I haven't ran across websites that serves up HDR images, I am not sure I would notice the difference. WebP seems appropriately named and optimized for image delivery on the web.
Maybe you are thinking of high bit depth for archival use? I can see some use cases there where 8-bit is not sufficient, though personally I store high bit depth images in whatever raw format was produced by my camera (which is usually some variant of TIFF).
8-bit can have banding even without "HDR". Definitely not enough. 10 bit HDR video is becoming more common, and popularity for images will follow. Adoption is hampered by the fact that Windows has bad HDR support, but it all works plenty well on macOS and mobile platforms.
It would be nice if everything was non tone-mapped HDR all the time for software, and the windowing system or the monitor would do the (local) tone mapping.
No, you don't want that. You want your windowing system & UI/graphics layers working in display native range (see eg, Apple's EDR). The consistency of appearance of the SDR range is too important to leave it up to unknown tone mapping.
Also it's too power expensive to have your display in HDR if you're only showing SDR UIs, which not only is the common reality but will continue to be so for the foreseeable future.
Requiring every game, photo viewing app, drawing program, ... every application to decide how to do it's HDR->SDR seems unnecessary complication due to poor abstractions.
The locality of local tone mapping (the ideal approach to HDR->SDR mapping) would expose the window boundaries. Two photos or two halves of the same photo in different windows (as opposed to being in the same window) would create an artificial discontinuity for the correction fields being artificially contained within each window instead of spanning the users visual field as best as possible.
Every local tone mapping needs to make an assumption of the surrounding colors: is the window surrounded by black, gray, colored or bright light should influence how the tone mapping is done at borders. This information is not available for an app: it can only be done at the windowing system level or in the monitor.
The higher the quality of the HDR->SDR mapping in a system, the more opportunity there is to limit the maximum brightness, and thus also the opportunity for energy savings.
> Requiring every game [..] to decide how to do it's HDR->SDR seems unnecessary complication due to poor abstractions.
Games already do this regardless and it's part of their post processing pipelines that also govern aspects of their environmental look.
What's missing is HDR->Display which is why HDR games have you go through a clunky calibration process to attempt to reverse out what the display is going to the PQ signal, when what the game actually wants is what MacOS/iOS and now Android just give them - the exact amount of HDR headroom which the display doesn't manipulate.
As for your other examples, being able to target the display native range doesn't mean you have to. Every decent os has a compositor API that lets you offload this to the system.
Yes, if local tone mapping is done by the operating system (windowing system or the monitor itself), then there is a chance that borders of windows are done appropriately within their spatial context.
For things where you actually care about lossless you probably also don't care about HDR.
HDR is (or can be) good for video & photography, but it's absolutely ass for UI.
Besides, you can just throw a gainmap approach at it if you really care. Works great with jpeg, and gainmaps are being added to heif & avif as well, no reason jpegxl couldn't get the same treatment. The lack of "true 10-bit" is significantly less impactful at that point
Gainmaps don't solve 8-bit mach banding. If anything you get more banding: two bandings, one banding from each of the two 8-bit fields multiplied together.
Gainmaps "solve" the problem of computing a local tone mapping by declaring that it needs to be done at server side or at image creation time rather than at viewing time.
My prediction: Gainmaps are going to be too complex of a solution for us as a community and we are going to find something else that is easier. Perhaps we could end up standardizing a small set of local tone mapping algorithms applied at viewing time.
> Gainmaps "solve" the problem of computing a local tone mapping by declaring that it needs to be done at server side or at image creation time rather than at viewing time.
Which was already the case. A huge amount of phone camera quality is from advanced processing, not sensor improveds. Trying to get that same level of investment in all downstream clients is both unrealistic and significantly harder. A big aspect of why DolbyVision looks better is just Dolby forces everyone to use their tone mapping, and client consistency is critical.
Gainmaps also avoid the proprietary metadata disaster that plaugues HLG/PQ video content.
> If anything you get more banding: two bandings, one banding from each of the two 8-bit fields multiplied together.
The math works out such that you get the equivalent of something like 9 bits of depth but you're also not wasting bits on colors and luminance ranges you aren't using like you are with bt2020 hlg or PQ
I didn't try it out, but I don't see the 9 bit coming. I feel it gives about 7.5 bits.
Mixing two independent quantization sources will lead to more error.
Some decoding systems such as traditional jpeg does not specify results exactly so bit-perfect quantization-aware compensation is not going to be possible.
The context of this thread is lossless webp, there aren't any compression artifacts to deal with.
Go try the math out, the theoretical is higher than 9 bits but 8.5-9 bit equivalent is very achievable in practice. With two lossless 8 bit sources this is absolutely adequate for current displays, especially since again you're not wasting bits on things like PQ's absurd range.
Will this be added to webp? Probably not, it seems like a dead format regardless. But 8 bit isn't the death knell for HDR support as is otherwise believed.
You just cannot reach the best quality with 8 bits, not in SDR, not in HDR, not with gainmap HDR. Sometimes you don't care for a particular use case, and then 8 bits becomes acceptable. Many use cases remain where degradation by a compression system is unacceptable or creates too many complications.
Find me a single example of a UI in HDR for the UI components, not for photos/videos.
> Even SDR needs 10-bit in a lot of situations to not have banding.
You've probably been looking at 10-bit HDR content on an 8-bit display panel anyway (true 10-bit displays don't exist in mobile yet, for example). 8-bits works fine with a bit of dithering
Yes, but the place where you want dithering is in the display, not in the image. Dithering doesn't work with compression because it's exactly the type of high frequency detail that compression removes. It's much better to have a 10 bit image which makes the information low frequency (and lets the compression do a better job since a 10 bit image will naturally be more continuous than an 8 bit image since there is less rounding error in the pixels), and let the display do the dithering at the end.
Gainmaps only take a lot of space if implemented poorly in the software creating the gainmap. On Pixel phones they take up 2% of the image size, by being stored in quarter resolution and scaling back up during decoding, which works fine on all gainmap-supported devices.
They're more prone to banding, but it's definitely not a problem with all images.
I guess I should say, take up lots of space unless you're OK with lower quality. In any case, gainmaps are entirely unrelated to the 8 bit vs 10 bit question. The more range you have (gamut or brightness) the worse 8 bit is, regardless of whether you're using a gainmap or not. And you can use gainmaps with 10 bit images.
I would, at a first blush, disagree with that characterization? Dialogue equals more fine-grained strokes and more individual, independent “zones” to encode.
IIRC the way you encode grayscale in WebP is a SUBTRACT_GREEN transform that makes the red and blue channel 0 everywhere, and then use a 1-element prefix code for R and B, so the R and B for each pixel take zero bits. Same idea with A for opaque images. Do you know why that's not good enough?
If I had just added 128 to the residuals, all remaining prediction arithmetic would have worked better and it would have given 1 % more density.
This is because most related arithmetic for predicting pixels is done in unsigned 8 bit arithmetic. Subtract green moves such predictions to often cross the 0 -> 255 boundary, and then averaging, deltas etc make little sense and add to the entropy.
WebP also has a near-lossless encoding mode based on lossless WebP specification that is mostly unadvertised, but should be preferred over real lossless in almost every use case. Often you can half the size without additional visible loss.
Is this mode picked automatically in "mixed" mode?
Unfortunately, that option doesn't seem to be available in gif2webp (I mostly use WebP for GIF images - as animated AVIF support is poor on browsers and that has an impact in interoperability)
Not in gif2webp, no. It is available in img2webp as a global (not per-frame) option. It looks like when you pass it, it will be used for all lossless encoding, including when "-mixed" tries the lossless mode.
WebP near-lossless is very far in compression density against that kind of visually lossless. Still 2-3x more bits I think. No reason to compare. The near-lossless (at settings 60 and 80) is closer to pixel perfect no matter how much you zoom, whereas Jon's "visually lossless" is what I'd rather call usual very high quality lossy without pixel precision guarantees.
If we replace those heuristics with a search that tries out which of the values is closest to the original, we should get better quality, especially at the lowest bitrates where smoothing is important.
It is unlikely that there will be any bitstream changes in JPEG XL. There is still a lot of potential for encoder improvements within the current bitstream, both for lossy and for lossless.
Last time I tested cwebp it did not handle (PNG) color spaces correctly so the result of a supposedly lossless conversion actually looked different from the original. What good is better lossless compression if it is not actually lossless visually?
It is ironic you said this because when I disabled webp in my browser because it had a huge security vulnerability, Discord was the only site which broke and didn't immediately just serving me more reasonable image formats.
I've always thought that one as flying under the radar. Most get stuck on WebP not offering tangible enough benefits (or even worse) over MozJPEG encoding, but WebP _lossless_ is absolutely fantastic for performance/speed! PNG or even OptiPNG is far worse. And very well supported online now, and leaving the horrible lossless AVIF in the dust too of course.