JPEG XL vs. AVIF for web use-cases(jakearchibald.com) |
JPEG XL vs. AVIF for web use-cases(jakearchibald.com) |
JPEG XL doesn't have that benefit, while sites adoption is arguably a worse issue than browser adoption.
To demonstrate the point even for AVIF itself - it has been in the browsers for a while. Can you use it on common sites? Good luck if you can, even major sites like GitHub and GitLab have issues with it due to some site code depending on hardcoded list of known formats or other similar problems.
ISO-BMFF container is bloated and needlessly complicated. AVIF decoders didn't even want to reuse existing MP4 libraries for it due to all the baggage it brings, and implemented their own minimal parsers.
AVIF would have been better off with a simple wrapper similar to RIFF/PNG or extending AV1's own OBU header (which for inexplicable reason gets its data duplicated inside the HEIF container and then implementations are required to verify that both copies agree!)
I hope AVIF will skip AV2. We don't need yet another almost-identical format to migrate to.
Many other image formats are. AVIF uses HEIC, the same container that HEIF does.
> when AV2, AV3 etc. will come out, there won't be a need to go through another very difficult phase of sites adoption - it will still be AVIF just with newer codec inside, and it will be just up to browsers to catch up on newer versions and newer codecs will address technical needs as times goes.
Fingers crossed, but AV2-based AVIF specs haven't even been finalized, so who knows.
With no codec for a new compression algorithm, it does not matter if the browser can read the container, you still see the "broken image" icon on your display.
I also remember the big claims about WebP's superiority, which ended-up in practice, at equivalent file-size, mostly trading away some of the JPEG artifacts that we all know for some unusual new ones.
I don't think there's a large-enough margin in this space that a new format could chew into to make the general public care: image compression seems like a solved problem overall. The second best thing is to come-up with a format that can make the content producers not have to care either, i.e. be the best in class or close-enough in a variety of use-cases (lossy, lossless, fast, animated, hdr, progressive, …). My naive impression was that jxl is mostly interesting in that regard.
ffmpeg -i {input_file} -filter_complex "[0:v]format=pix_fmts=yuva444p,split[color][alpha];[alpha]alphaextract[alpha_chan]" -map "[color]" -map "[alpha_chan]" -c:v libaom-av1 -crf 25 -cpu-used 3 -still-picture 1 -aom-params "sharpness=2:enable-chroma-deltaq=1:arnr-strength=0" -color_range pc -colorspace bt709 -color_primaries bt709 -color_trc bt709 {output_file}Granted, AVIF performs impressively for, say, a huge hero image for a blog where you're out to create an overall impression and people aren't going to look at it closely. It does not impress me when I am compressing photos I took with my mirrorless and I expect them to look like photos taken with a mirrorless and not cell phone snaps.
https://jakearchibald.com/2020/avif-has-landed/demos/compare...
I was talking about. He linked another one! Guess people finally realized that one sucks and now they have a new one. I screwed up.
That's what I noticed anyway, not a car or photo guy either.
You're looking at it in a browser that doesn't support JPEG XL, so it's falling back to a WASM renderer, and I think it handles resizing differently.
This is totally my bad. I thought I was doing a good thing by adding that fallback renderer, but it isn't identical and it's giving people the wrong impression.
The lossless version is JPEG XL, hence the difference to AVIF.
After reading this article, there's something to point to prove I'm not going crazy.
libjxl's slow speed at efforts >7 is primarily due to an iterative evaluation-optimization loop of a perceptual error metric called Butteraugli (by tuning quantization weights). This, as well as some other computations in libjxl encoding, happen to be data-parallel and run faster on GPUs than multicore CPUs.
In case anyone is interested, I've been working on a GPU-accelerated libjxl port (supporting CUDA and Metal for now) that makes this much faster, closer to libjxl's normal speeds: https://github.com/yunho-c/gjxl - geared for encoding a large batch images into JPEG XL. It's also faster by around 2.9x at normal effort (7).
This is something I've felt doesn't get enough attention when comparing JXL and AVIF. AVIF can be the replacement for GIF.
><video muted autoplay> is right there.
>No, I'm not adding a demo. I don't want it on my server. Use video formats for video.
I'm not sure if "Use video formats for video" is saying to use AVIF over JXL or saying to use AV1 over AVIF. If the latter, GIF-like animations have a different enough user expectation that it makes sense to have it as something different from regular videos. Even <video muted autoplay> doesn't encode the full expected behavior because GIFs are not expected to have controls like pause, play and scrub. And even if you hide the controls users will expect similar behavior when opening it in an image viewer or in a new tab. Images do not have controls so they fit better as an image, although maybe they need their own category.
Also, I didn't realize how good AVIF was at progressive rendering. I don't think I knew it could do that at all. I think AVIF is the clear winner for the web, although it is still nice to have JXL for lossless. Somehow I feel that AVIF still hasn't gained as much usage as it should, especially now that it is supported almost everywhere. I think I see more webp than AVIF, and JPEG is still everywhere. Maybe now that JXL is out, developers will take another look? AVIF is supported by 96.35%-98.83% of browsers according to caniuse whereas webp is 97.18%-99.68% and JPEG is 97.28%-99.78%.
I also didn't know there was a Rust JXL encoder named jixel.[0]
Though given the lagging speed in decoding, is there a faster tying JXL decoder planned?
(also like the BPP size metric that is picture size-independent)
Wish that widget with improvements (that allows comparison of 3 pics with 3 buttons: original/codec1/codec2) were the widespread standard (also, "hold" is a rather unergonomic action)
Otherwise, seems like AVIF has had impressive gains in both speed and quality, wonder whether JXL could catch up
For a wide variety of usecases, not for every isolated usecase. Today, AVIF is better for showing people ads^W^W^W web content delivery. This article is titled “JPEG XL vs. AVIF for web use-cases”. The other article recently discussed¹ is subtitled “Investigating JPEG XL's place as a Web image codec” and ends:
> JPEG XL isn't useless; it is genuinely compelling technology for use cases beyond the Web.
¹ https://news.ycombinator.com/item?id=49690554
(Either way, can we agree to take webp out behind the barn?)
JPEG-XL seems to be the best solution for storing and distributing high-quality images. For myself, I want high-quality images, so JPEG-XL is what matters, both for new images and for compressing the old archives of JPEG images.
While I have my own Web server, it is for private use and not for commercial purposes, so I have no interest in using AVIF to achieve the smallest image sizes, but at a lower quality than I want.
What optimizations are being added? I thought it was basically the exact same codec, but different packaging and usually some adjustment to how the encoder is tuned.
Overall I am getting that AVIF is better on the web...unless Lossless is needed, in that case better take JPEGXL.
It does seem like AVIFs win on small images, and JXL gives you progressive rendering, easy upgradability on JPEGs, and better lossless and high bitrate images.
IE never supported AVIF. Edge even shipped AVIF later than Chrome. One of the leaders of JPEG XL worked at Google until relatively recently. A massive amount of JPEG XL development has been done by a team at Google.
So, is animated AVIF only keyframes / p-frames, where each frame is independent from the other? I was under that impression, uncertain if there are any other capabilities it might have (like only updating part of the canvas when only parts change, like GIF supports)
2. Is it possible to encode AVIF with hardware acceleration?
When it comes to hardware encoders, the nicest thing you can say about them is they're fast. Software tends to do way better at quality. Hardware AV1 encoders will be tuned for video rather than stills.
It's hard to rigorously judge a codec from a handful images, especially given the large impact they would have (with a widely adopted codec encoding bazillions of images in the coming years).
* There are many intricate details that go into codecs and visual perception. For instance, our sensitivity to visual errors are dependent on colors (all of hue, saturation, and brightness), spatial frequency of artifacts, local contrast and texture presence, et cetera.
And like OP mentioned, perceptual error metrics (including SSIMULACRA2) aren't perfectly representative of human-evaluated visual quality. For instance, libjxl deliberately makes choices that hurt SSIMU2 scores, but improve human-rated quality.
But yes, you can see this with jixel, which I'm really impressed by, but it's so tuned to SSIMU2 that it looks really bad to human eyes in some cases compared to libjxl.
But that is correct and why any proper study should first train the participants on the type of artifacts and trade-offs. Like the reference to JXL choices: think its creator mentioned that AVIF might look nicer for faces because it was "smoothing" them but it was a worse representation of the original. So the study participants would need to be conscious of that trade off and be clear in terms of what they're asked to evaluate - whether the result looks nicer or whether it represents the original better.
Maybe the first step to designing better encoders is to build an extremely accurate visuoperceptual error metric. Seems like ML's rapid progress haven't caught onto it just yet.
I am still on webp, thinking that I am on the bleeding edge in a world where artworkers are obsessed with pixels with JPG/PNG as the only formats they know, which is an advance on GIF.
Every browser advertises what formats it will accept and if it is in 'data-saving, low bandwidth mode', so I just configure the CDN to keep the names the same '.jpg' but to send the bestest format for the situation/browser, whether that be webp or AVIF, fetching super-high resolution files from the origin server, outputting them in 'retina' resolution with none of those 'picture' elements referencing half a dozen 'responsive' sizes.
In this way nobody has to care what image format is being served, and if it is deemed that everything is way too compressed, the CDN can be flushed of the cached images, quality increased, and cache rebuilt.
It looks like I will need to update my server configuration to use JPEG XL in the usual five years' time, given the lack of any revolutionary benefit.
I was at Google for 10 years, then went to Shopify for 2 years, but I missed the web. For most of the time I was at Google, it mostly did what was good for the web, rather than pushing Google's interests, but that started to change, which is one of things that led to me leaving. E.g. see what happened with the Prompt API.
And the article supports what I have said.
Quotation from the article:
> But JPEG XL catches up at very high quality. Around SSIMULACRA2 85, libjxl's default matches AVIF's default, and at maximum efforts, jixel 'extraslow' is ~6% smaller than AVIF s0. jixel 'slow' is 10–13% smaller than AVIF's default from SSIMULACRA2 80 upwards.
Perhaps we can use clever experiment design to address it, like doing a "full-reference" evaluation (e.g., pick most similar two images, out of encoder A, encoder B, and original) rather than strictly A/B.
