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* [[Cloudflare]] announced AVIF support in a blog post on 3 October 2020.<ref>{{Cite web|date=3 October 2020|title=AVIF image format supported by Cloudflare Image Resizing|url=https://blog.cloudflare.com/generate-avif-images-with-image-resizing/|website=The Cloudflare Blog|access-date=3 October 2020|archive-date=3 October 2020|archive-url=https://web.archive.org/web/20201003135712/https://blog.cloudflare.com/generate-avif-images-with-image-resizing/|url-status=live}}</ref>
* [[Cloudflare]] announced AVIF support in a blog post on 3 October 2020.<ref>{{Cite web|date=3 October 2020|title=AVIF image format supported by Cloudflare Image Resizing|url=https://blog.cloudflare.com/generate-avif-images-with-image-resizing/|website=The Cloudflare Blog|access-date=3 October 2020|archive-date=3 October 2020|archive-url=https://web.archive.org/web/20201003135712/https://blog.cloudflare.com/generate-avif-images-with-image-resizing/|url-status=live}}</ref>
* [[Vimeo]] announced AVIF support in a blog post on June 3, 2021.<ref>{{Cite web |url=https://medium.com/vimeo-engineering-blog/upgrading-images-on-vimeo-620f79da8605 |title=Archived copy |access-date=3 June 2021 |archive-date=3 June 2021 |archive-url=https://web.archive.org/web/20210603150425/https://medium.com/vimeo-engineering-blog/upgrading-images-on-vimeo-620f79da8605 |url-status=live }}</ref>
* [[Vimeo]] announced AVIF support in a blog post on June 3, 2021.<ref>{{Cite web |url=https://medium.com/vimeo-engineering-blog/upgrading-images-on-vimeo-620f79da8605 |title=Archived copy |access-date=3 June 2021 |archive-date=3 June 2021 |archive-url=https://web.archive.org/web/20210603150425/https://medium.com/vimeo-engineering-blog/upgrading-images-on-vimeo-620f79da8605 |url-status=live }}</ref>
* avif.io is a dedicated database tracking support status on AVIF.<ref>{{Cite web|date=14 August 2021|title=avif.io AVIF converter|url=https://avif.io|website=avif.io}}</ref>
'''Programming languages'''
'''Programming languages'''
* [[PHP]] version 8.1 will include AVIF support in its GD extension.<ref>{{Cite web|date=14 June 2021|title=PHP 8.1: GD: AVIF image support|url=https://php.watch/versions/8.1/gd-avif|website=PHP.Watch|access-date=14 June 2021|archive-date=14 June 2021|archive-url=https://web.archive.org/web/20210614080825/https://php.watch/versions/8.1/gd-avif|url-status=live}}</ref>
* [[PHP]] version 8.1 will include AVIF support in its GD extension.<ref>{{Cite web|date=14 June 2021|title=PHP 8.1: GD: AVIF image support|url=https://php.watch/versions/8.1/gd-avif|website=PHP.Watch|access-date=14 June 2021|archive-date=14 June 2021|archive-url=https://web.archive.org/web/20210614080825/https://php.watch/versions/8.1/gd-avif|url-status=live}}</ref>

Revision as of 17:41, 10 October 2021

AOMedia Video 1
Internet media typevideo/AV1, video/webm; codecs="av01.*"
Developed byAlliance for Open Media
Initial release28 March 2018; 6 years ago (2018-03-28)
Latest release
1.0.0 Errata 1[1]
8 January 2019; 5 years ago (2019-01-08)
Type of formatVideo coding format
Contained by
Extended from
Extended toAVIF
StandardAOM AV1
Free format?Yes
Websiteaomedia.org/av1-features/ Edit this at Wikidata

AOMedia Video 1 (AV1) is an open, royalty-free video coding format initially designed for video transmissions over the Internet. It was developed as a successor to VP9 by the Alliance for Open Media (AOMedia),[2] a consortium founded in 2015 that includes semiconductor firms, video on demand providers, video content producers, software development companies and web browser vendors. The AV1 bitstream specification includes a reference video codec.[1] In 2018, Facebook conducted testing that approximated real world conditions, and the AV1 reference encoder achieved 34%, 46.2% and 50.3% higher data compression than libvpx-vp9, x264 high profile, and x264 main profile respectively.

Like VP9, but unlike H.264/AVC and HEVC, AV1 has a royalty-free licensing model that does not hinder adoption in open-source projects.[3][4][5][6][2][7]

AV1 Image File Format (AVIF) is an image file format that uses AV1 compression algorithms.

History

The Alliance's motivations for creating AV1 included the high cost and uncertainty involved with the patent licensing of HEVC, the MPEG-designed codec expected to succeed AVC.[8][6] Additionally, the Alliance's seven founding members – Amazon, Cisco, Google, Intel, Microsoft, Mozilla and Netflix – announced that the initial focus of the video format would be delivery of high-quality web video.[9] The official announcement of AV1 came with the press release on the formation of the Alliance for Open Media on 1 September 2015. Only 42 days before, on 21 July 2015, HEVC Advance's initial licensing offer was announced to be an increase over the royalty fees of its predecessor, AVC.[10] In addition to the increased cost, the complexity of the licensing process increased with HEVC. Unlike previous MPEG standards where the technology in the standard could be licensed from a single entity, MPEG-LA, when the HEVC standard was finished, two patent pools had been formed with a third pool was on the horizon. In addition, various patent holders were refusing to license patents via either pool, increasing uncertainty about HEVC's licensing. According to Microsoft's Ian LeGrow, an open-source, royalty-free technology was seen as the easiest way to eliminate this uncertainty around licensing.[8]

The negative effect of patent licensing on free and open-source software has also been cited as a reason for the creation of AV1.[6] For example, building an H.264 implementation into Firefox would prevent it from being distributed free of charge since licensing fees would have to be paid to MPEG-LA.[11] Free Software Foundation Europe has argued that FRAND patent licensing practices make the free software implementation of standards impossible due to various incompatibilities with free software licenses.[7]

Many of the components of the AV1 project were sourced from previous research efforts by Alliance members. Individual contributors started experimental technology platforms years before: Xiph's/Mozilla's Daala already published code in 2010, Google's experimental VP9 evolution project VP10 was announced on 12 September 2014,[12] and Cisco's Thor was published on 11 August 2015. Building on the code base of VP9, AV1 incorporates additional techniques, several of which were developed in these experimental formats.[13] The first version 0.1.0 of the AV1 reference codec was published on 7 April 2016.

Although a soft feature freeze came into effect at the end of October 2017, development continued on several significant features. One of these in-progress features, the bitstream format, was projected to be frozen in January 2018 but was delayed due to unresolved critical bugs as well as further changes to transformations, syntax, the prediction of motion vectors, and the completion of legal analysis.[citation needed] The Alliance announced the release of the AV1 bitstream specification on 28 March 2018, along with a reference, software-based encoder and decoder.[14] On 25 June 2018, a validated version 1.0.0 of the specification was released.[15] On 8 January 2019 a validated version 1.0.0 with Errata 1 of the specification was released.

Martin Smole from AOM member Bitmovin said that the computational efficiency of the reference encoder was the greatest remaining challenge after the bitstream format freeze had been completed.[16] While still working on the format, the encoder was not targeted for production use and speed optimizations were not prioritized. Consequently, the early version of AV1 was orders of magnitude slower than existing HEVC encoders. Much of the development effort was consequently shifted towards maturing the reference encoder. In March 2019, it was reported that the speed of the reference encoder had improved greatly and within the same order of magnitude as encoders for other common formats.[17]

On 21 January 2021, the MIME type of AV1 was defined as video/AV1. The usage of AV1 using this MIME type is restricted to Real-time Transport Protocol purposes only.[18]

Purpose

AV1 aims to be a video format for the web that is both state of the art and royalty free.[2] According to Matt Frost, head of strategy and partnerships in Google's Chrome Media team, «the mission of the Alliance for Open Media remains the same as the WebM project».[19]

A recurring concern in standards development, not least of royalty-free multimedia formats, is the danger of accidentally infringing on patents that their creators and users didn't know about. The concern has been raised regarding AV1,[20] and previously VP8,[21] VP9,[22] Theora[23] and IVC.[24] The problem is not unique to royalty-free formats, but it uniquely threatens their status as royalty-free.

Patent licensing AV1, VP9, Theora HEVC, AVC GIF, MP3, MPEG-1, MPEG-2, MPEG-4 Part 2
By known patent holders Royalty-free Royalty bearing Patents expired
By unknown patent holders Impossible to ascertain until the format is old
enough that any patents would have expired
(at least 20 years in WTO countries)

To fulfill the goal of being royalty free, the development process requires that no feature can be adopted before it has been confirmed independently by two separate parties to not infringe on patents of competing companies. In cases where an alternative to a patent-protected technique is not available, owners of relevant patents have been invited to join the Alliance (even if they were already members of another patent pool). For example, Alliance members Apple, Cisco, Google, and Microsoft are also licensors in MPEG-LA's patent pool for H.264.[20] As an additional protection for the royalty-free status of AV1, the Alliance has a legal defense fund to aid smaller Alliance members or AV1 licensees in the event they are sued for alleged patent infringement.[20][5][25]

Under patent rules adopted from the World Wide Web Consortium (W3C), technology contributors license their AV1-connected patents to anyone, anywhere, anytime based on reciprocity (i.e. as long as the user does not engage in patent litigation).[26] As a defensive condition, anyone engaging in patent litigation loses the right to the patents of all patent holders.[citation needed][27]

This treatment of intellectual property rights (IPR), and its absolute priority during development, is contrary to extant MPEG formats like AVC and HEVC. These were developed under an IPR uninvolvement policy by their standardization organisations, as stipulated in the ITU-T's definition of an open standard. However, MPEG's chairman has argued this practice has to change,[28] which it is:[citation needed] EVC is also set to have a royalty-free subset,[29][30] and will have switchable features in its bitstream to defend against future IPR threats.[citation needed]

The creation of royalty-free web standards has been a long-stated pursuit for the industry. In 2007, the proposal for HTML5 video specified Theora as mandatory to implement. The reason was that public content should be encoded in freely implementable formats, if only as a "baseline format", and that changing such a baseline format later would be hard because of network effects.[31] The Alliance for Open Media is a continuation of Google's efforts with the WebM project, which renewed the royalty-free competition after Theora had been surpassed by AVC. For companies such as Mozilla that distribute free software, AVC can be difficult to support as a per-copy royalty easily is unsustainable given the lack of revenue stream to support these payments in free software (see FRAND § Excluding costless distribution).[3] Similarly, HEVC has not successfully convinced all licensors to allow an exception for freely distributed software (see HEVC § Provision for costless software).

The performance goals include "a step up from VP9 and HEVC" in efficiency for a low increase in complexity. NETVC's efficiency goal is 25% improvement over HEVC.[32] The primary complexity concern is for software decoding, since hardware support will take time to reach users. However, for WebRTC, live encoding performance is also relevant, which is Cisco's agenda: Cisco is a manufacturer of videoconferencing equipment, and their Thor contributions aim at "reasonable compression at only moderate complexity".[33]

Feature wise, AV1 is specifically designed for real-time applications (especially WebRTC) and higher resolutions (wider color gamuts, higher frame rates, UHD) than typical usage scenarios of the current generation (H.264) of video formats, where it is expected to achieve its biggest efficiency gains. It is therefore planned to support the color space from ITU-R Recommendation BT.2020 and up to 12 bits of precision per color component.[34] AV1 is primarily intended for lossy encoding, although lossless compression is supported as well.[35]

Technology

AV1 is a traditional block-based frequency transform format featuring new techniques. Based on Google's VP9,[36] AV1 incorporates additional techniques that mainly give encoders more coding options to enable better adaptation to different types of input.

Processing stages of an AV1 encoder with relevant technologies associated with each stage.
libaom
Developer(s)Alliance for Open Media
Stable release
3.1.3[37] / 5 October 2021; 3 years ago (2021-10-05)
Written inC, assembly
LicenseBSD 2-Clause License (free software)
Websiteaomedia.googlesource.com/aom

The Alliance published a reference implementation written in C and assembly language (aomenc, aomdec) as free software under the terms of the BSD 2-Clause License.[38] Development happens in public and is open for contributions, regardless of AOM membership.

The development process was such that coding tools were added to the reference code base as experiments, controlled by flags that enable or disable them at build time, for review by other group members as well as specialized teams that helped with and ensured hardware friendliness and compliance with intellectual property rights (TAPAS). When the feature gained some support in the community, the experiment was enabled by default, and ultimately had its flag removed when all of the reviews were passed.[39] Experiment names were lowercased in the configure script and uppercased in conditional compilation flags.[citation needed]

To better and more reliably support HDR and color spaces, corresponding metadata can now be integrated into the video bitstream instead of being signaled in the container.

Partitioning

10 ways for subpartitioning coding units – into squares (recursively), rectangles, or mixtures thereof ("T-shaped").

Frame content is separated into adjacent same-sized blocks referred to as superblocks. Similar to the concept of a macroblock, superblocks are square-shaped and can either be of size 128×128 or 64×64 pixels. Superblocks can be divided in smaller blocks according to different partitioning patterns. The four-way split pattern is the only pattern whose partitions can be recursively subdivided. This allows superblocks to be divided into partitions as small as 4×4 pixels.

Diagram of the AV1 superblock partitioning. It shows how 128×128 superblocks can be split all the way down to 4×4 blocks. As special cases, 128×128 and 8×8 blocks can't use 1:4 and 4:1 splits, and 8×8 blocks can't use "T"-shaped splits.

"T-shaped" partitioning patterns are introduced, a feature developed for VP10, as well as horizontal or vertical splits into four stripes of 4:1 and 1:4 aspect ratio. The available partitioning patterns vary according to the block size, both 128×128 and 8×8 blocks can't use 4:1 and 1:4 splits. Moreover, 8×8 blocks can't use "T" shaped splits.

Two separate predictions can now be used on spatially different parts of a block using a smooth, oblique transition line (wedge-partitioned prediction).[citation needed] This enables more accurate separation of objects without the traditional staircase lines along the boundaries of square blocks.

More encoder parallelism is possible thanks to configurable prediction dependency between tile rows (ext_tile).[40]

Prediction

AV1 performs internal processing in higher precision (10 or 12 bits per sample), which leads to compression improvement due to smaller rounding errors in reference imagery.

Predictions can be combined in more advanced ways (than a uniform average) in a block (compound prediction), including smooth and sharp transition gradients in different directions (wedge-partitioned prediction) as well as implicit masks that are based on the difference between the two predictors. This allows combination of either two inter predictions or an inter and an intra prediction to be used in the same block.[41][citation needed]

A frame can reference 6 instead of 3 of the 8 available frame buffers for temporal (inter) prediction while providing more flexibility on bi-prediction[42] (ext_refs[citation needed]).

Warped motion as seen from the front of a train.

The Warped Motion (warped_motion)[40] and Global Motion (global_motion[citation needed]) tools in AV1 aim to reduce redundant information in motion vectors by recognizing patterns arising from camera motion.[40] They implement ideas that were tried to be exploited in preceding formats like e.g. MPEG-4 ASP, albeit with a novel approach that works in three dimensions. There can be a set of warping parameters for a whole frame offered in the bitstream, or blocks can use a set of implicit local parameters that get computed based on surrounding blocks.

Switch frames (S-frame) are a new inter-frame type that can be predicted using already decoded reference frames from a higher-resolution version of the same video to allow switching to a lower resolution without the need for a full keyframe at the beginning of a video segment in the adaptive bitrate streaming use case.[43]

Intra prediction

Intra prediction consists of predicting the pixels of a given blocks only using information available in the current frame. Most often, intra predictions are built from the neighboring pixels above and to the left of the predicted block. The DC predictor builds a prediction by averaging the pixels above and to the left of block.

Directional predictors extrapolate these neighboring pixels according to a specified angle. In AV1, 8 main directional modes can be chosen. These modes start at an angle of 45 degrees and increase by a step size of 22.5 degrees up until 203 degrees. Furthermore, for each directional mode, six offsets of 3 degree can be signaled for bigger blocks, three above the main angle and three below it, resulting in a total of 56 angles (ext_intra).

The "TrueMotion" predictor got replaced with a Paeth predictor which looks at the difference from the known pixel in the above left corner to the pixel directly above and directly left of the new one and then chooses the one that lies in direction of the smaller gradient as predictor. A palette predictor is available for blocks with very few (up to 8, dominant) colors like in some computer screen content. Correlations between the luminosity and the color information can now be exploited with a predictor for chroma blocks that is based on samples from the luma plane (cfl).[40] In order to reduce visible boundaries along borders of inter-predicted blocks, a technique called overlapped block motion compensation (OBMC) can be used. This involves extending a block's size so that it overlaps with neighboring blocks by 2 to 32 pixels, and blending the overlapping parts together.[44]

Data transformation

To transform the error remaining after prediction to the frequency domain, AV1 encoders can use square, 2:1/1:2, and 4:1/1:4 rectangular DCTs (rect_tx),[42] as well as an asymmetric DST[45][46][47] for blocks where the top and/or left edge is expected to have lower error thanks to prediction from nearby pixels, or choose to do no transform (identity transform).

It can combine two one-dimensional transforms in order to use different transforms for the horizontal and the vertical dimension (ext_tx).[40][42]

Quantization

AV1 has new optimized quantization matrices (aom_qm).[48] The eight sets of quantization parameters that can be selected and signaled for each frame now have individual parameters for the two chroma planes and can use spatial prediction. On every new superblock, the quantization parameters can be adjusted by signaling an offset.

Filters

For the in-loop filtering step, the integration of Thor's constrained low-pass filter and Daala's directional deringing filter has been fruitful: The combined Constrained Directional Enhancement Filter (cdef[citation needed]) exceeds the results of using the original filters separately or together.[citation needed]

It is an edge-directed conditional replacement filter that smooths blocks with configurable (signaled) strength roughly along the direction of the dominant edge to eliminate ringing artifacts.

There is also the loop restoration filter (loop_restoration) based on the Wiener filter and self-guided restoration filters to remove blur artifacts due to block processing.[40]

Film grain synthesis (film_grain) improves coding of noisy signals using a parametric video coding approach. Due to the randomness inherent to film grain noise, this signal component is traditionally either very expensive to code or prone to get damaged or lost, possibly leaving serious coding artifacts as residue. This tool circumvents these problems using analysis and synthesis, replacing parts of the signal with a visually similar synthetic texture, based solely on subjective visual impression instead of objective similarity. It removes the grain component from the signal, analyzes its non-random characteristics, and instead transmits only descriptive parameters to the decoder, which adds back a synthetic, pseudorandom noise signal that's shaped after the original component. It is the visual equivalent of the Perceptual Noise Substitution technique used in AC3, AAC, Vorbis, and Opus audio codecs.

Entropy coding

Daala's entropy coder (daala_ec[citation needed]), a non-binary arithmetic coder, was selected for replacing VP9's binary entropy coder. The use of non-binary arithmetic coding helps evade patents, but also adds bit-level parallelism to an otherwise serial process, reducing clock rate demands on hardware implementations.[citation needed] This is to say that the effectiveness of modern binary arithmetic coding like CABAC is being approached using a greater alphabet than binary, hence greater speed, as in Huffman code (but not as simple and fast as Huffman code). AV1 also gained the ability to adapt the symbol probabilities in the arithmetic coder per coded symbol instead of per frame (ec_adapt).[40]

Scalable video coding

Of main importance to video conferencing, scalable video coding is a general technique, not unique to AV1, of restricting and structuring video frame dependencies so that one or more lower bitrate video streams are extractable from a higher bitrate stream with better quality. This differs from adaptive bitrate streaming in that some compression efficiency in each higher bitrate adaptation is given up for the benefit of that of the overall stream. The encoding process is also less redundant and demanding.

AV1 has provisions for temporal and spatial scalability.[49] This is to say that both framerate and resolution are usable ways to define a lower bitrate substream.

Quality and efficiency

A first comparison from the beginning of June 2016[50][by whom?] found AV1 roughly on par with HEVC, as did one using code from late January 2017.[51]

In April 2017, using the 8 enabled experimental features at the time (of 77 total), Bitmovin was able to demonstrate favorable objective metrics, as well as visual results, compared to HEVC on the Sintel and Tears of Steel short films.[52] A follow-up comparison by Jan Ozer of Streaming Media Magazine confirmed this, and concluded that "AV1 is at least as good as HEVC now".[53] Ozer noted that his and Bitmovin's results contradicted a comparison by Fraunhofer Institute for Telecommunications from late 2016[54] that had found AV1 65.7% less efficient than HEVC, underperforming even H.264/AVC which they concluded as being 10.5% more efficient. Ozer justified this discrepancy by having used encoding parameters endorsed by each encoder vendor, as well as having more features in the newer AV1 encoder.[54] Decoding performance was at about half the speed of VP9 according to internal measurements from 2017.[43]

Tests from Netflix in 2017, based on measurements with PSNR and VMAF at 720p, showed that AV1 was about 25% more efficient than VP9 (libvpx).[55] Tests from Facebook conducted in 2018, based on PSNR, showed that the AV1 reference encoder was able to achieve 34%, 46.2% and 50.3% higher data compression than libvpx-vp9, x264 high profile, and x264 main profile respectively.[56][57]

Tests from Moscow State University in 2017 found that VP9 required 31% and HEVC 22% more bitrate than AV1 in order to achieve similar levels of quality.[58] The AV1 encoder was operating at a speed "2500–3500 times lower than competitors" due to the lack of optimization (which was not available at that time).[59]

Tests from University of Waterloo in 2020 found that when using a mean opinion score (MOS) for 2160p (4K) video AV1 had bitrate saving of 9.5% compared to HEVC and 16.4% compared to VP9. They also however concluded that at the time of the study at 2160p the AV1 video encodes on average took 590× longer compared to encoding with AVC; while HEVC took on average 4.2× longer and VP9 took on average 5.2× longer than AVC respectively.[60][61]

The latest encoder comparison by Streaming Media Magazine as of September 2020, which used moderate encoding speeds, VMAF, and a diverse set of short clips, indicated that the open-source libaom and SVT-AV1 encoders took about twice as long time to encode as x265 in its "veryslow" preset while using 15-20% less bitrate, or about 45% less bitrate than x264 veryslow. The best-in-test AV1 encoder, Visionular's Aurora1, in its "slower" preset, was as fast as x265 veryslow while saving 50% bitrate over x264 veryslow.[62]

Profiles and levels

Profiles

AV1 defines three profiles for decoders which are Main, High, and Professional. The Main profile allows for a bit depth of 8- or 10-bits per sample with 4:0:0 (greyscale) and 4:2:0 (quarter) chroma sampling. The High profile further adds support for 4:4:4 chroma sampling (no subsampling). The Professional profile extends capabilities to full support for 4:0:0, 4:2:0, 4:2:2 (half) and 4:4:4 chroma sub-sampling with 8, 10 and 12 bit color depths.[14]

Feature comparison between AV1 profiles
Main (0) High (1) Professional (2)
Bit depth 8 or 10-bit 8 or 10-bit 8, 10 & 12 bit
Chroma subsampling 4:0:0 Yes Yes Yes
4:2:0 Yes Yes Yes
4:2:2 No No Yes
4:4:4 No Yes Yes

Levels

AV1 defines levels for decoders with maximum variables for levels ranging from 2.0 to 6.3.[63] The levels that can be implemented depend on the hardware capability.

Example resolutions would be 426×240@30 fps for level 2.0, 854×480@30 fps for level 3.0, 1920×1080@30 fps for level 4.0, 3840×2160@60 fps for level 5.1, 3840×2160@120 fps for level 5.2, and 7680×4320@120 fps for level 6.2. Level 7 has not been defined yet.[64]

seq_level_idx Level MaxPicSize
(Samples)
MaxHSize
(Samples)
MaxVSize
(Samples)
MaxDisplayRate
(Hz)
MaxDecodeRate
(Hz)
MaxHeader
Rate (Hz)
MainMbps
(Mbit/s)
HighMbps
(Mbit/s)
Min Comp Basis Max Tiles Max Tile Cols Example
0 2.0 147456 2048 1152 4,423,680 5,529,600 150 1.5 - 2 8 4 426×240@30fps
1 2.1 278784 2816 1584 8,363,520 10,454,400 150 3.0 - 2 8 4 640×360@30fps
4 3.0 665856 4352 2448 19,975,680 24,969,600 150 6.0 - 2 16 6 854×480@30fps
5 3.1 1065024 5504 3096 31,950,720 39,938,400 150 10.0 - 2 16 6 1280×720@30fps
8 4.0 2359296 6144 3456 70,778,880 77,856,768 300 12.0 30.0 4 32 8 1920×1080@30fps
9 4.1 2359296 6144 3456 141,557,760 155,713,536 300 20.0 50.0 4 32 8 1920×1080@60fps
12 5.0 8912896 8192 4352 267,386,880 273,715,200 300 30.0 100.0 6 64 8 3840×2160@30fps
13 5.1 8912896 8192 4352 534,773,760 547,430,400 300 40.0 160.0 8 64 8 3840×2160@60fps
14 5.2 8912896 8192 4352 1,069,547,520 1,094,860,800 300 60.0 240.0 8 64 8 3840×2160@120fps
15 5.3 8912896 8192 4352 1,069,547,520 1,176,502,272 300 60.0 240.0 8 64 8 3840×2160@120fps
16 6.0 35651584 16384 8704 1,069,547,520 1,176,502,272 300 60.0 240.0 8 128 16 7680×4320@30fps
17 6.1 35651584 16384 8704 2,139,095,040 2,189,721,600 300 100.0 480.0 8 128 16 7680×4320@60fps
18 6.2 35651584 16384 8704 4,278,190,080 4,379,443,200 300 160.0 800.0 8 128 16 7680×4320@120fps
19 6.3 35651584 16384 8704 4,278,190,080 4,706,009,088 300 160.0 800.0 8 128 16 7680×4320@120fps

Supported container formats

Standardized

  • ISO Base Media File Format:[65] the ISOBMFF containerization spec by AOMedia was the first to be finalized and the first to gain adoption. This is the format used by YouTube.
  • Matroska: version 1 of the Matroska containerization spec[66] was published in late 2018.[67]

Unfinished standards

  • MPEG Transport Stream (MPEG TS)[68]
  • Real-time Transport Protocol: a preliminary RTP packetization spec by AOMedia defines the transmission of AV1 OBUs directly as the RTP payload.[49] It defines an RTP header extension that carries information about video frames and their dependencies, which is of general usefulness to § scalable video coding. The carriage of raw video data also differs from for example MPEG TS over RTP in that other streams, such as audio, must be carried externally.

Not standardized

  • WebM: as a matter of formality, AV1 has not been sanctioned into the subset of Matroska known as WebM as of late 2019.[69]
  • On2 IVF: this format was inherited from the first public release of VP8, where it served as a simple development container.[70] rav1e also supports this format.[71]
  • Pre-standard WebM: Libaom featured early support for WebM before Matroska containerization was specified; this has since been changed to conform to the Matroska spec.[72]

Adoption

Content providers

In October 2016, Netflix stated they expected to be an early adopter of AV1.[73] On 5 February 2020, Netflix began using AV1 to stream select titles on Android, providing 20% improved compression efficiency over their VP9 streams.[74]

In 2018, YouTube began rolling out AV1, starting with its AV1 Beta Launch Playlist. According to the description, the videos are (to begin with) encoded at high bitrate to test decoding performance, and YouTube has "ambitious goals" for rolling out AV1. YouTube for Android TV supports playback of videos encoded in AV1 on capable platforms as of version 2.10.13, released in early 2020.[75]

In February 2019, Facebook, following their own positive test results, said they would gradually roll out AV1 as soon as browser support emerges, starting with their most popular videos.[56]

In June 2019, Vimeo's videos in the "Staff picks" channel were available in AV1.[76] Vimeo is using and contributing to Mozilla's Rav1e encoder and expects, with further encoder improvements, to eventually provide AV1 support for all videos uploaded to Vimeo as well as the company's "Live" offering.[76]

On 30 April 2020, iQIYI announced support for AV1 for users on PC web browsers and Android devices, according to the announcement, as the first Chinese video streaming site to adopt the AV1 format.[77]

Twitch plans to roll out AV1 for its most popular content in 2022 or 2023, with universal support projected to arrive in 2024 or 2025.[78]

Software implementations

  • Libaom is the reference implementation. It includes an encoder (aomenc) and a decoder (aomdec). As the former research codec, it has the advantage of being made to justifiably demonstrate efficient use of every feature, but at the general cost of encoding speed. At feature freeze, the encoder had become problematically slow, but speed optimizations with negligible efficiency impact have continued to be made also after that.[79][17]
  • rav1e is an encoder written in Rust and assembly.[71] rav1e takes the opposite developmental approach to Aomenc: start out as the simplest (therefore fastest) conforming encoder, and then improve efficiency over time while remaining fast.[79]
  • SVT-AV1 includes an open-source encoder and decoder first released by Intel in February 2019 that is designed especially for usage on data center servers based on Intel Xeon processors. Netflix collaborates with Intel on SVT-AV1.[80][81]
  • dav1d is a decoder written in C99 and assembly focused on speed and portability.[82] The first official version (0.1) was released in December 2018.[83] Version 0.2 was released in March 2019, with users able to "safely use the decoder on all platforms, with excellent performance", according to the developers.[84] Version 0.3 was announced in May 2019 with further optimizations demonstrating performance 2 to 5 times faster than aomdec.;[85] version 0.5 was released in October 2019.[86] Firefox 67 switched from Libaom to dav1d as a default decoder in May 2019.[87] In 2019, dav1d v0.5 was rated the best decoder in comparison to libgav1 and libaom.[88] dav1d 0.9.0 was released on May 17, 2021.[89] dav1d 0.9.2 was released on September 3, 2021.[90]
  • Cisco AV1 is a proprietary live encoder that Cisco developed for its Webex teleconference products. The encoder is optimized for latency[91] and the constraint of having a "usable CPU footprint", as with a "commodity laptop".[92] Cisco stressed that at their operating point – high speed, low latency – the large toolset of AV1 does not preclude a low encoding complexity.[91] Rather, the availability of tools for screen content and scalability in all profiles enabled them to find good compression-to-speed tradeoffs, better even than with HEVC.[92] Compared to their previously deployed H.264 encoder, a particular area of improvement was in high resolution screen sharing.[91]
  • libgav1 is a decoder written in C++11 released by Google.

Several other parties have announced to be working on encoders, including EVE for AV1 (in beta testing),[93] NGCodec,[94] Socionext,[95] Aurora[96] and MilliCast.[97]

Software support

Web browsers

Video players

Encoders

Video editors

Others

Operating system support

AV1 support by different operating systems
Microsoft Windows macOS BSD / Linux Chrome OS Android iOS
Codec support Not enabled by default, requires add-on No Yes Yes Yes No
Container support ISO base media file format (.mp4)
WebM (.webm)
Matroska (.mkv)
No ISO base media file format (.mp4)
WebM (.webm)
Matroska (.mkv)
ISO base media file format (.mp4)
WebM (.webm)
Matroska (.mkv)
No
Notes - Support introduced in Windows 10 October 2018 Update (1809) with AV1 Video Extension add-on[103]

- Support for hardware acceleration added in Windows 10 November 2019 Update (1909)[116]

- Supported in Universal Windows Platform apps like Microsoft Edge and Films & TV

Unsupported as of macOS Catalina Supports decoding, from Chrome OS 70 onward Supported since Android 10[117][118][119] Unsupported as of iOS 14

Hardware

Comparison of AV1 hardware
Product Function
(D = Decode, E = Encode)
Profile Throughput
(single core)
Throughput
(max)
Ref
Allegro AL-E195 E Main (0) and
Professional (1)
[120]
AL-E210 E Main (0) 4K 30fps 10-bit ? [121][122]
AMD RDNA 2 D Main (0) 8K [123][124][125]
Amlogic S905X4 D 4K 120fps [126]
S908X D 8K 60fps
S805X2 D 1080p
Amphion CS8142 D 4K 60fps [127]
Broadcom BCM7218X D 4K [128]
Chips&Media WAVE510A
WAVE627[129]
D
E
Main (0) 4K 60fps 4K 120fps [130]
Dwango E 720p 30fps [131]
Intel Tiger Lake
Rocket Lake
Alder Lake
D Main (0) 8K 10-bit[132] [133][134][124][135]
MediaTek Dimensity 900
Dimensity 1000
Dimensity 1100
Dimensity 1200
D 4K 60fps 4K 60fps [136][137][138]
MT9638 D 4K 60fps 10-bit 4K 60fps 10-bit [139]
Nvidia GeForce 30 D Main (0) 8K 60fps 10-bit [140][124][141]
Realtek RTD1311 D 4K [142]
RTD2893 D 8K [143][144]
Rockchip RK3588 D 4K 60fps 10-bit [145]
Samsung Exynos 2100 D [146]

Several Alliance members demonstrated AV1 enabled products at IBC 2018,[147][148] including Socionext's hardware accelerated encoder. According to Socionext, the encoding accelerator is FPGA based and can run on an Amazon EC2 F1 cloud instance, where it runs 10 times faster than existing software encoders.

According to Mukund Srinivasan, chief business officer of AOM member Ittiam, early hardware support will be dominated by software running on non-CPU hardware (such as GPGPU, DSP or shader programs, as is the case with some VP9 hardware implementations), as fixed-function hardware will take 12–18 months after bitstream freeze until chips are available, plus 6 months for products based on those chips to hit the market.[39] The bitstream was finally frozen on 28 March 2018, meaning chips could be available sometime between March and August 2019.[20] According to the above forecast, products based on chips could then be on the market at the end of 2019 or the beginning of 2020.

  • On 7 January 2019, NGCodec announced AV1 support for NGCodec accelerated with Xilinx FPGAs.[94]
  • On 18 April 2019, Allegro DVT announced its AL-E210 multi-format video encoder hardware IP, the first publicly announced hardware AV1 encoder.[149][121]
  • On 23 April 2019, Rockchip announced their RK3588 SoC which features AV1 hardware decoding up to 4K 60fps at 10-bit color depth.[145]
  • On 9 May 2019, Amphion announced a video decoder with AV1 support up to 4K 60fps[150] On 28 May 2019, Realtek announced the RTD2893, its first integrated circuit with AV1 decoding, up to 8K.[143][144]
  • On 17 June 2019, Realtek announced the RTD1311 SoC for set-top boxes with an integrated AV1 decoder.[142]
  • On 20 October 2019, a roadmap from Amlogic shown 3 set-top box SoCs that are able to decode AV1 content, the S805X2, S905X4 and S908X.[151] The S905X4 was used in the SDMC DV8919 by December.[152]
  • On 21 October 2019, Chips&Media announced the WAVE510A VPU supporting decoding AV1 at up to 4Kp120.[153]
  • On 26 November 2019, MediaTek announced world's first smartphone SoC with an integrated AV1 decoder.[137] The Dimensity 1000 is able to decode AV1 content up to 4K 60fps.
  • On 3 January 2020, LG Electronics announced that its 2020 8K TVs, which are based on the α9 Gen 3 processor, support AV1.[154][155]
  • At CES 2020, Samsung announced that its 2020 8K QLED TVs, featuring Samsung's "Quantum Processor 8K SoC," are capable of decoding AV1.[156]
  • On 13 August 2020, Intel announced that their Intel Xe-LP GPU in Tiger Lake will be their first product to include AV1 fixed-function hardware decoding.[135][134]
  • On 1 September 2020, Nvidia announced that their Nvidia GeForce RTX 30 Series GPUs will support AV1 fixed-function hardware decoding.[140]
  • On 2 September 2020, Intel officially launched Tiger Lake 11th Gen CPUs with AV1 fixed-function hardware decoding.[157]
  • On 15 September 2020, AMD merged patches into the amdgpu drivers for Linux which adds support for AV1 decoding support on RDNA2 GPUs.[123][158][159]
  • On 28 September 2020, Roku refreshed the Roku Ultra including AV1 support.[160]
  • On 30 September 2020, Intel released version 20.3.0 for the Intel Media Driver which added support for AV1 decoding on Linux.[132][133][161]
  • On 10 October 2020, Microsoft confirmed support for AV1 hardware decoding on Xe-LP(Gen12), Ampere and RDNA2 with a blog post.[124]
  • On 16 March 2021, Intel officially launched Rocket Lake 11th Gen CPUs with AV1 fixed-function hardware decoding.[162]

Patent claims

Sisvel, a Luxembourg-based company, has formed a patent pool, and are selling a patent license for AV1. The pool was announced in early 2019,[163] but a list of claimed patents was first published on 10 March 2020.[164] This list contains over 1050 patents.[164] The substance of the patent claims remains to be challenged.[165]

Sisvel's prices are .32 Euros for display devices and .11 Euros for non-display devices using AV1. Sisvel has stated that they won't seek content royalties, but their license makes no exemption for software.[164][165]

As of March 2020, the Alliance for Open Media has not responded to the list of patent claims. Their statement after Sisvel's initial announcement reiterated the commitment to their royalty-free patent license and made mention of the "AOMedia patent defense program to help protect AV1 ecosystem participants in the event of patent claims", but did not mention the Sisvel claim by name.[166]

Google is aware of the patent pool, but does not plan to alter their current or upcoming usage plans of AV1.[167]

AV1 Image File Format (AVIF)

AV1 Image File Format (AVIF) (/əˈvf/[citation needed]) is an image file format specification for storing images or image sequences compressed with AV1 in the HEIF file format.[168] It competes with HEIC which uses the same container format, built upon ISOBMFF, but HEVC for compression. Version 1.0.0 of the AVIF specification was finalized in February 2019.

AVIF supports features like:

libavif
Developer(s)Alliance for Open Media
Stable release
0.9.2 / 23 June 2021; 3 years ago (2021-06-23)
Written inC, assembly
LicenseBSD 2-Clause License (free software)
Websitegithub.com/AOMediaCodec/libavif

AVIF support

On 14 December 2018 Netflix published the first .avif sample images.[171] On November 2020, HDR sample images with PQ transfer function and BT.2020 color primaries have been published.[172]

Software

  • Web browsers
    • AVIF support in web browsers is in development. Notably:[173]
    • In August 2020, Google Chrome version 85 was released with full AVIF support.[174] Google Chrome 89 for Android adds AVIF support.[175]
    • In October 2021, Mozilla Firefox 93 was released with default AVIF support.[176] It had planned to enable AVIF support by default in Firefox 86, but pulled the change a day before release.[177][178]
    • Webkit added AVIF support on March 5, 2021.[179]
    • Brave
  • Image viewers
  • Media player
    • VLC reads AVIF files starting with version 4, which is still in development[183]
  • Image editors
    • Paint.net added support for opening AVIF files in September 2019,[184] and the ability to save AVIF format images in an August 2020 update.[185]
    • The Colorist format conversion and Darktable RAW image data have each released support for and provide reference implementations of libavif.
    • A GIMP plugin implementation has been developed supporting both 3.x and 2.10.x plugin APIs. Native AVIF import and export was added to GIMP in October 2020.[186]
  • Image libraries
    • libavif - Portable library for encoding and decoding AVIF files.
    • libheif - ISO/IEC 23008-12:2017 HEIF and AVIF decoder and encoder.
    • SAIL - Format-agnostic library with support of AVIF implemented on top of libavif.

OS

  • Microsoft announced support with the Windows 10 "19H1" preview release, including support in File Explorer, Paint and multiple APIs, together with sample images.[187]
  • Android 12 released on October 4, 2021 added native support for AVIF, although it will not be the default image format for the camera app.[188]

Websites

  • On 14 February 2020, Netflix published a blog article with objective measurements on AVIF's image quality & compression efficiency in comparison to JPEG.[189]
  • Cloudflare announced AVIF support in a blog post on 3 October 2020.[190]
  • Vimeo announced AVIF support in a blog post on June 3, 2021.[191]
  • avif.io is a dedicated database tracking support status on AVIF.[192]

Programming languages

  • PHP version 8.1 will include AVIF support in its GD extension.[193]

Others

  • Exiftool supports AVIF format for read and write EXIF since v11.79.

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