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Picture Codec Comparability

Picture Codec Comparability

2023-03-18 14:56:15

Picture Codec Comparability


Mar 16, 2023





To begin issues off, I’ve been a fan of the AVIF picture format since I heard about it, not lengthy after I began studying concerning the AV1 video codec in 2020. I figured the truth that it was backed by the Alliance for Open Media, was the pure successor to WebP, and was based mostly on a fairly highly effective video codec that was quickly rising in reputation was nice for customers & organizations alike to simply perceive what the know-how stood for, the place it got here from, and what advantages it supplied over the prevailing lossy picture king, JPEG. Good codecs are open supply codecs, so the truth that AVIF was open supply was a giant deal to me as properly. It is usually already widely supported on the time of writing. I assumed unequivocally that AVIF could be the way forward for pictures on the net once I first realized about it. I do not assume I used to be totally fallacious, however I hadn’t but heard of JPEG-XL.

JPEG-XL (JXL for brief) is a picture codec by the JPEG committee (sure, the JPEG committee). Initially I hadn’t thought a lot of the codec as a result of the compression effectivity was “the identical as AVIF,” so I form of wrote it off, as I am positive many uninformed individuals have & proceed to do. Upon doing extra analysis, my place flipped and I discovered myself deeply invested in the way forward for JXL.

JXL’s fascinating options embrace the extremely environment friendly variable-blocksize discrete cosine remodel (which is superior to JPEG’s DCT), utilization of the XYB colorspace which extra precisely represents the response our cones in our eyeballs should completely different wavelengths of sunshine, & a “modular” mode for environment friendly lossless or near-lossless coding. It is usually used whereas encoding lossy JPEG-XL pictures, however I do not know a lot about it & I will not faux to. At present the reference encoder additionally helps patch detection, noise synthesis, and can (in all probability) finally assist spline detection as it’s current within the codec specification. JPEG-XL additionally helps lossless JPEG transcoding that reduces the filesize of JPEGs which for my part is a game-changing characteristic. That alone may very well be a revolutionary codec by itself. Progressive decode can be a standout characteristic of JPEG-XL, and I discovered this article very attention-grabbing relating to that.

Some extra attention-grabbing JXL articles & assets:

Additionally value noting is the format’s most outspoken pioneer Jon Sneyers (co-author of the JPEG XL spec) in addition to different noteworthy builders are extraordinarily lively inside the neighborhood and worth the suggestions of the people who find themselves captivated with their work. This shouldn’t be as distinctive as it’s, however it’s extremely worthwhile to have one’s voice heard so simply & continuously by builders who really care. I commend Sneyers & the opposite core JXL devs for this.

Anyway, TL;DR: JXL has much more to supply than simply good compression. However, I nonetheless want to know; how does it stack up towards different picture codecs relating to lossy compression & lossless compression?

Methodology (Photographic Corpus)

With the intention to produce an unbiased take a look at to find out how good JPEG-XL is relative to my wants, I took 27 photographs (principally consisting of panorama/structure pictures) round my seaside hometown utilizing my Sony a5000 at 20.1mp, edited them in Darktable, exported them as 16-bit sRGB PNGs (AdobeRGB had some problems), & lastly I ran a script written by my good friend RootAtCali (try their cool site) to find out every picture format’s SSIMULACRA2 scores for every high quality degree accessible through the format’s lossy coding choice.

I will be sure to make my lossless sources accessible through an edit to this publish, & they will be linked on the high. Within the meantime, this is another page with full decision lossy JXL photographs encoded at -d 1.0. The pictures are beneath CC-BY-SA 4.0.

These assessments had been run utilizing the SSIMULACRA2 visible high quality metric through ssimulacra2_rs. This metric is designed to mannequin human imaginative and prescient much better than VMAF, SSIM, PSNR, & different much less efficient options. By way of the readme on Github:

Returns a rating in vary -inf..100, which correlates to subjective visible high quality scores as follows:

  • 30 = low high quality. This corresponds to the p10 worst output of mozjpeg -quality 30.
  • 50 = medium high quality. This corresponds to the typical output of cjxl -q 40 or mozjpeg -quality 40, or the p10 output of cjxl -q 50 or mozjpeg -quality 60.
  • 70 = prime quality. This corresponds to the typical output of cjxl -q 65 or mozjpeg -quality 70, p10 output of cjxl -q 75 or mozjpeg -quality 80.
  • 90 = very prime quality. Doubtless unattainable to tell apart from the unique when considered at 1:1 from a standard viewing distance. This corresponds to the typical output of mozjpeg -quality 95 or the p10 output of cjxl -q 95.

Due to the irrelevance of unfavourable SSIMULACRA2 scores, I finished the vertical axis on the graph(s) at 0.

For context, this is an summary of the picture codecs examined:

  • JPEG, the reigning champ. has been used for many years. Helps progressive decode
  • WebP, based mostly on VP8, an open-source video codec.
  • JPEG-XL, the designated successor to JPEG. Designed by the JPEG committee.
  • AVIF, based mostly on AV1, a contemporary open-source video codec.

This is a helpful chart supplied by Cloudinary.

Notably absent are JPEG 2000 (J2K) & HEIC. Contemplating JXL is J2K’s successor & J2K by no means noticed widespread adoption, I am unsure together with it helps anyone. HEIC is being excluded as a result of it sucks, & is also notably not royalty free.

Listed here are the encoders examined for every format:

  • JPEG through the mozjpeg encoder
  • JPEG through the mozjpeg encoder, tuned for MS-SSIM, utilizing the ‘Tuned for MS-SSIM on Kodak picture set’ quantization desk & arithmetic coding
  • JPEG through the elusive & mysterious jpegli encoder (extra on this later)
  • WebP through cwebp
  • JPEG-XL through the libjxl reference encoder implementation, cjxl
  • AVIF through aom-av1-lavish, tuned for SSIM

This is the encoder parameters I used, together with the encoder model (in the identical order as above)

cjpeg -q [quality] "enter" > "output.jpg" | mozjpeg model 4.1.1 (construct 20230217)

cjpeg -q [quality] -quant-table 2 -tune-ms-ssim -arithmetic "enter" > "output.jpg" | mozjpeg model 4.1.1 (construct 20230217)

benchmark_xl --input=[input] --codec=jpeg:enc-jpegli:rgb:q[quality] --save_compressed --output_dir=[outdir] | cjxl v0.9.0 c4927fbf

cwebp -m 6 -q [quality] "enter" -o [output.webp] | 1.3.0 libsharpyuv: 0.2.0

cjxl "enter" "output.jxl" -q [quality] -e 7 --brotli_effort 11 | cjxl v0.9.0 c4927fbf

avifenc -c aom -s 6 -j 16 -d 10 -y 444 --min 1 --max 63 -a end-usage=q -a cq-level=[quality] -a tune=ssim "enter" "output.avif" | AOMedia Venture AV1 Encoder Psy v3.6.0 (default)

WebP is at most effort & the JPEG encoders had been left inventory by way of effort. cjxl is on effort 7 (the interior default, so I did not really want to specify it, & brotli_effort is just for lossless iirc), & we encode avif at pace 6 as a result of it correlates finest with JXL’s default pace (& can be rav1e’s default pace internally though we’re not utilizing rav1e). Aviator, based mostly on SVT-AV1, consciously defaults to hurry 6 for AV1 video encoding, as does rav1e-based rAV1ator.

See Also

Benchmarking with this picture dataset gave us a complete of slightly below 18,000 information factors earlier than averaging. For the graph, I calculated the arithmetic imply of the bpp & SSIMULACRA2 rating for every high quality step for every encoder.

Listed here are the outcomes:


Now, maintain your breath, conclusions come on the finish!

Methodology (Non-photographic)

This can be a shorter take a look at with much less occurring, however nonetheless attention-grabbing & value mentioning. I am utilizing this picture to check non-photographic encoding utilizing the identical parameters as above. Listed here are the outcomes:


Whereas this is just one picture, I’ve universally seen AVIF take a fairly giant lead with each non-photographic picture I’ve examined.

Lossless? Animation?

Keep tuned! Whereas each AVIF & JXL (in addition to WebP) assist animation, I would prefer to cowl that in a distinct publish. I would prefer to study extra about how AVIF & JXL work relative to lossless picture coding as properly earlier than I sort out a take a look at like that.


The place does JPEG-XL win?

It’s clear to me that JPEG-XL goes to be my alternative for exporting my novice pictures. It performs exceptionally properly at increased high quality, outperforming AVIF & the others by a big margin. AVIF is stronger as high quality decreases, however AVIF is additional weakened by the truth that encoding utilizing extra threads usually hurts effectivity & encoding an AVIF picture is usually slower than encoding a JXL picture. As for the opposite plethora of options JXL has to supply, AVIF can barely compete. AVIF can be hampered by its decrease most picture dimensions in comparison with competing codecs.

The place does AVIF win?

AVIF wins at low to medium (perhaps low-medium) high quality. That is nice for content material devilery on the net, as pictures do not all the time have to be excessive constancy or retain a ton of high-frequency element to keep up their attraction; one thing that appears pleasing and resembles the supply might be extra fascinating. Even supposing AVIF lacks progressive decode, its superior coding effectivity at decrease high quality considerably makes up for this for my part. AVIF can be the winner for our non-photographic picture, and when you belief that picture is not an edge case, it opens up some cool alternatives for sharing digital artwork as JXL does not have an encoder accessible with spline detection to compete proper now. Being based mostly on the AV1 video codec, AVIF is allegedly simpler to implement as properly; the codec’s widespread adoption sees it already attaining a level of success on the Net.

How concerning the others?

WebP is not superb for my part, plumetting at increased high quality & being soundly defeated by AVIF at decrease high quality. JPEG clearly nonetheless has potential even years later, and MS-SSIM tuning appears to do the encoder some favors with the photographic dataset. The jpegli encoder borrows a few of JXL’s fancy coding strategies to enhance JPEG high quality even additional, particularly at increased high quality. I did not even take a look at jpegli with the superior XYB colorspace (as this proved onerous to do), which to my eyes nets jpegli an excellent higher high quality enchancment over normal jpeg encoders. There is a cool Twitter thread about this. In line with Jyrki Alakuijala, “jpegli helps greater than 8 bits per channel (round 10.5 bits) and may codify HDR dynamics (HLG/PQ/XYB/and so on.) within the outdated ‘8-bit’ format.” This appears extraordinarily promising.


I need a internet the place each AVIF & JPEG-XL can exist, and builders resolve which format to make use of for its deserves. Google’s Chromium crew has rejected JXL assist for Chrome, and Mozilla stays “impartial,” on JXL, preserving a flag in Firefox Nightly to allow partial assist. The Chromium crew should not have absolutely the authority to shoot down would-be requirements like this, because it appears they’re the only decision-maker on this house & all others should comply with their lead. In my view, JPEG-XL & AVIF have basically completely different strengths which lend them to completely different use circumstances. Contemplating JXL has been endorsed by Fb, Adobe, Intel and the Video Electronics Requirements Affiliation, The Guardian, Flickr and SmugMug, Shopify, the Krita Basis, Serif Ltd, Gaia Sky, and plenty of extra, the market is most actually . My present optimistic hope is that JXL takes off exterior the net amongst professionals working with instruments just like the Adobe suite or options, and digital camera producers, smartphone OEMS, and others take discover & start to consider JXL extra severely. The advantages can’t be ignored, and it’s (for my part) the one picture format that’s in each approach superior to JPEG & provides a concrete future for the various current JPEGs on the Net & past.

Whereas it is a non-scientific take a look at, please share this publish if you would like to see JPEG-XL get extra consideration for its deserves. AVIF is already broadly supported, I need not struggle for it; JPEG-XL nonetheless has a warfare to be gained, and I would like anybody who desires higher pictures & a greater Net to be on JXL’s aspect in addition to AVIF’s, and to know that JPEG-XL wants our help as customers to achieve widespread adoption. This is what I would suggest doing proper now:

Utilizing Chrome or one other Chromium-based browser? Contemplate switching to Thorium. It’s accessible for almost each platform, together with Home windows, Linux, macOS, and Android, and has full JXL assist. It is going to sync together with your Google account identical to Chrome will. It is usually faster.

Utilizing Firefox? Not a foul alternative. In case your workflow permits, switching to Firefox Nightly for informal looking & enabling the JXL flag for partial JXL assist by looking out ‘jxl’ in about:config just isn’t a foul choice. I am hooked up to Firefox myself, & utilizing the flag on my telephone works nice for many issues that do not make use of an alpha channel or HDR.

If you would like to try some lovely JXL pictures, you possibly can head here. You’ll be able to take a look at your browser’s JXL assist here. Bear in mind, the Net will be the final platform with no proprietor, and we have to hold it that approach.

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