Comparison of video codecs

Α video codec is software or a device that provides encoding and decoding for digital video, and which may or may not include the use of video compression and/or decompression. Most codecs are typically implementations of video coding formats.
The compression may employ lossy data compression, so that quality-measurement issues become important. Shortly after the compact disc became widely available as a digital-format replacement for analog audio, it became feasible to also store and use video in digital form. A variety of technologies soon emerged to do so. The primary goal for most methods of compressing video is to produce video that most closely approximates the fidelity of the original source, while simultaneously delivering the smallest file-size possible. However, there are also several other factors that can be used as a basis for comparison.

Introduction to comparison

The following characteristics are compared in video codecs comparisons:Video quality per bitrate. Commonly video quality is considered the main characteristic of codec comparisons. Video quality comparisons can be subjective or objective.Performance characteristics such as compression/decompression speed, supported profiles/options, supported resolutions, supported rate control strategies, etc.General software characteristics – for example:

* Manufacturer
* Supported OS
* Version number
* Date of release
* Type of license
* Supported interfaces
* Price

Video quality

The quality the codec can achieve is heavily based on the compression format the codec uses. A codec is not a format, and there may be multiple codecs that implement the same compression specification – for example, MPEG-1 codecs typically do not achieve quality/size ratio comparable to codecs that implement the more modern H.264 specification. But quality/size ratio of output produced by different implementations of the same specification can also vary.
Each compression specification defines various mechanisms by which raw video can be reduced in size, from simple bit compression to psycho-visual and motion summarization, and how the output is stored as a bit stream. So long as the encoder component of the codec adheres to the specification, it can choose any combination of these methods to apply different parts of the content. The decoder component of a codec that also conforms to the specification recognizes each of the mechanisms used, and thus interprets the compressed stream to render it back into raw video for display. Each encoder implements the specification according to its own algorithms and parameters, which means that the compressed output of different codecs will vary, resulting in variations in quality and efficiency between them.
Prior to comparing codec video-quality, it is important to understand that every codec can give a varying degree of quality for a given set of frames within a video sequence. Numerous factors play a role in this variability. First, all codecs have a bitrate control mechanism that is responsible for determining the bitrate and quality on a per-frame basis. A difference between variable bitrate and constant bitrate creates a trade-off between a consistent quality over all frames, on the one hand, and a more constant bitrate, which is required for some applications, on the other. Second, some codecs differentiate between different types of frames, such as key frames and non-key frames, differing in their importance to overall visual quality and the extent to which they can be compressed. Third, quality depends on prefiltrations, which are included on all present-day codecs. Other factors may also come into play.
For a sufficiently long clip, it is possible to select sequences that have suffered little from the compression, and sequences that have suffered heavily, especially if CBR has been used, whereby the quality between frames can vary highly due to different amounts of compression needed to achieve a constant bitrate. So, in a given long clip, such as a full-length movie, any two codecs may perform quite differently on a particular sequence from the clip, while the codecs may be approximately equal in quality over a wider sequence of frames. Press-releases and amateur forums may sometimes select sequences known to favor a particular codec or style of rate-control in reviews.

Objective video quality

Objective video evaluation techniques are mathematical models that seek to predict human judgments of picture quality, as often exemplified by the results of subjective quality assessment experiments. They are based on criteria and metrics that can be measured objectively and automatically evaluated by a computer program. Objective methods are classified based on the availability of an original pristine video signal, which is considered to be of high quality. Therefore, they can be classified as:Full reference methods, where the whole original video signal is availableReduced reference methods, where only partial information of the original video is available, andNo-reference methods, where the original video is not available at all.

Subjective video quality

This is concerned with how video is perceived by a viewer, and designates their opinion on a particular video sequence. Subjective video quality tests are quite expensive with regard to time and human resources.
There are many ways of showing video sequences to experts and recording their opinions. A few of them have been standardized, mainly in ITU-R Recommendation BT.500-13 and ITU-T Recommendation P.910.
The reason for measuring subjective video quality is the same as for measuring the mean opinion score for audio. Opinions of experts can be averaged and the average mark stated as, or accompanied by, a given confidence interval. Additional procedures can be used for averaging. For example, experts whose opinions are considered unstable may have their opinions rejected.
In the case of video codecs, this is a very common situation. When codecs with similar objective results show results with different subjective results, the main reasons can be:Pre- and postfilters are widely used in codecs. Codecs often use prefilters such as video denoising, deflicking, deshaking, etc. Denoising and deflicking normally maintain PSNR value while increasing visual quality. Deshaking greatly decreases PSNR, but increases visual quality. Postfilters show similar characteristics – deblocking and deringing maintain PSNR, but increase quality; graining essentially increases video quality, especially on big plasma screens, but decreases PSNR. All filters increase compression/decompression time, so they enhance visual quality but decrease the speed of coding and decoding.Motion estimation search strategy can also cause different visual quality for the same PSNR. So-called true motion search commonly will not reach minimum sum of absolute differences values in codec ME, but may result in better visual quality. Such methods also require more compression time.Rate control strategy. VBR commonly causes better visual quality marks than CBR for the same average PSNR values for sequences.
It is difficult to use long sequences for subjective testing. Commonly, three or four ten-second sequences are used, while full movies are used for objective metrics. Sequence selection is important – those sequences that are similar to the ones used by developers to tune their codecs are more competitive.

Performance comparison

Speed comparison

Number of frames per second commonly used for compression/decompression speed measurement.
The following issues should be considered when estimating probable codec performance differences:Decompression frame time uniformity – Big differences in this value can cause annoyingly jerky playback.SIMD support will vary by both processor and codec – e.g., MMX, SSE, SSE2, each of which changes CPU performance on some kinds of tasks.Multi-threading support varies substantially by processor, and codecs have different strategies for using those cores – the presence of Hyper-threading affects codec speed as it changes low-level resource allocation on the CPU.RAM speed – generally important for most codec implementations.Processor cache size – low values sometimes cause serious speed degradation, e.g., for CPUs with low caches such as several of the Intel Celeron series.GPU usage by codec – some codecs can drastically increase their performance by taking advantage of GPU resources.
So, for example, codec A may, on modern computers, give slower performance than codec B. Meanwhile, the same pair of codecs may give opposite results if running on an older computer with reduced memory resources.

Profiles support

Modern standards define a wide range of features and require very substantial software or hardware efforts and resources for their implementation. Only selected profiles of a standard are typically supported in any particular product.
The H.264 standard includes the following seven sets of capabilities, which are referred to as profiles, targeting specific classes of applications:Baseline Profile : Primarily for lower-cost applications with limited computing resources, this profile is used widely in videoconferencing and mobile applications.Main Profile : Originally intended as the mainstream consumer profile for broadcast and storage applications, the importance of this profile faded when the High profile was developed for those applications.Extended Profile : Intended as the streaming video profile, this profile has relatively high compression capability and some extra tricks for robustness to data losses and server stream switching.High Profile : The primary profile for broadcast and disc storage applications, particularly for high-definition television applications. High 10 Profile : Going beyond today's mainstream consumer product capabilities, this profile builds on top of the High Profile, adding support for up to 10 bits per sample of decoded picture precision.High 4:2:2 Profile : Primarily targeting professional applications that use interlaced video, this profile builds on top of the High 10 Profile, adding support for the 4:2:2 chroma sampling format while using up to 10 bits per sample of decoded picture precision.High 4:4:4 Predictive Profile : This profile builds on top of the High 4:2:2 Profile, supporting up to 4:4:4 chroma sampling, up to 14 bits per sample, and additionally supporting efficient lossless region coding and the coding of each picture as three separate color planes.Multiview High Profile: This profile supports two or more views using both inter-picture and MVC inter-view prediction, but does not support field pictures and macroblock-adaptive frame-field coding.
The standard also contains four additional all-Intra profiles, which are defined as simple subsets of other corresponding profiles. These are mostly for professional applications:High 10 Intra Profile: The High 10 Profile constrained to all-Intra use.High 4:2:2 Intra Profile: The High 4:2:2 Profile constrained to all-Intra use.High 4:4:4 Intra Profile: The High 4:4:4 Profile constrained to all-Intra use.CAVLC 4:4:4 Intra Profile: The High 4:4:4 Profile constrained to all-Intra use and to CAVLC entropy coding.
Moreover, the standard now also contains three Scalable Video Coding profiles.Scalable Baseline Profile: A scalable extension of the Baseline profile.Scalable High Profile: A scalable extension of the High profile.Scalable High Intra Profile: The Scalable High Profile constrained to all-Intra use.
An accurate comparison of codecs must take the profile variations within each codec into account.
''See also MPEG-2 Profiles and Levels.''

Supported rate control strategies

Videocodecs' rate control strategies can be classified as:

Variable bitrate and
Constant bitrate.

Variable bitrate is a strategy to maximize the visual video quality and minimize the bitrate. On fast-motion scenes, a variable bitrate uses more bits than it does on slow-motion scenes of similar duration, yet achieves a consistent visual quality. For real-time and non-buffered video streaming when the available bandwidth is fixed – e.g., in videoconferencing delivered on channels of fixed bandwidth – a constant bitrate must be used.
CBR is commonly used for videoconferences, satellite and cable broadcasting. VBR is commonly used for video CD/DVD creation and video in programs.
Bit rate control is suited to video streaming. For offline storage and viewing, it is typically preferable to encode at constant quality rather than using bit rate control.

Software characteristics

Codecs list

Codec

Creator/Maintainer

First public release date

Latest stable version

License

Patented compression formats

Compression method

Basic algorithm

OpenCL support

nVidia CUDA support

Intel SSE Support

Intel AVX support

Intel Quick Sync Video support

AOM Video 1

Alliance for Open Media

2018-06-25

1.0.0 Errata 1

Codec	macOS	other Unix & Unix-like	Windows
3ivx
Blackbird
Cinepak
DivX
FFmpeg
RealVideo
Schrödinger
Sorenson Video 3
Theora
x264
Xvid
Elecard

Name of comparison	Type of comparison	Date of publication	List of compared codecs	Comments
Series of Doom9 codec comparisons	Series of subjective comparison of popular codecs	2002 2003 2005	DivX4.12, On2 VP3, XviD 1/25 and WMV8 and DivX5.01, XviD 3/27 and ON2 VP4 – at first version Dirac, Elecard AVC HP, libavcodec MPEG-4, NeroDigital ASP, QuickTime 7, Snow, Theora, VideoSoft H.264 HP, XviD 1.1 beta 2 – in last one	Subjective comparison with convenient visualization
Series of MSU annual video codecs comparisons	Series of objective HEVC/AV1 codecs comparisons	2015 Oct. 2016 Aug. 2017 Sept. 2018 Sept.	2015: f265 H.265 Encoder, Intel MSS HEVC GAcc, Intel MSS HEVC Software, Ittiam HEVC Hardware Encoder, Ittiam HEVC Software Encoder, Strongene Lentoid HEVC Encoder, SHBP H.265 Real time encoder, x265, InTeleMax TurboEnc, SIF Encoder, VP9 Video Codec, x264 2016: Chips&Media HEVC Encoder, Intel MSS HEVC Encoder, Kingsoft HEVC Encoder, nj265, SHBPH.265 Real time encoder, x265, nj264, x264 2017: Kingsoft HEVC Encoder, nj265, NVIDIA NVENC SDK, Telecast, x265, AV1, nj264, SIF encoder, uAVS2, VP9, x264 2018: HW265, Intel MFX, Intel MFX, Kingsoft HEVC Encoder, sz265, Tencent Shannon Encoder, UC265, VITEC HEVC GEN2+, x265, AV1, SIF encoder, sz264, VP9, x264	Detailed objective comparisons
Series of MSU annual H.264 codecs comparisons	Series of objective H.264 codecs comparisons with MPEG-4 ASP reference	2004 2005 Jan. 2005 Dec. 2006 Dec. 2007 Dec. 2009 May 2010 Apr. 2011 May 2012 May 2013 Dec.	2005 : Mpegable AVC, Moonlight H.264, MainConcept H.264, Fraunhofer IIS, Ateme MPEG-4 AVC/H.264, Videosoft H.264, DivX Pro 5.1.1 2005 : DivX 6.0, ArcSoft H.264, Ateme H.264, ATI H.264, Elecard H.264, Fraunhofer IIS H.264, VSS H.264, x264 2006: DivX 6.2.5, MainConcept H.264, Intel H.264, VSS H.264, x264, Apple H.264,, Sorenson H.264 2007: XviD, MainConcept H.264, Intel H.264, x264, AMD H.264, Artemis H.264 2009: XviD, Dicas H.264, Elecard H.264, Intel IPP H.264, MainConcept H.264, x264 2010: XviD, DivX H.264, Elecard H.264, Intel MediaSDK AVC/H.264, MainConcept H.264, Microsoft Expression, Encoder, Theora, x264 2011: DivX H.264, Elecard H.264, Intel SandyBridge Transcoder, MainConcept H.264, MainConcept H.264, Microsoft Expression Encoder, DiscretePhoton, x264, VP8, XviD 2012: DivX H.264, Elecard H.264, Intel Ivy Bridge QuickSync, MainConcept H.264, MainConcept H.264, MainConcept H.264, DiscretePhoton, x264, XviD	Detailed objective comparisons
Series of Lossless Video Codecs Comparison	Two size and time comparisons of lossless codecs	2004 Oct. 2007 Mar.	2004 : Alpary v2.0, AVIzlib v2.2.3, CamStudio GZIP v1.0, CorePNG v0.8.2, FFV1 ffdshow 08/08/04, GLZW v1.01, HuffYUV v2.1.1, Lagarith v1.0.0.1, LEAD JPEG v1.0.0.1, LOCO v0.2, MindVid v1.0 beta 1, MSUlab beta v0.2.4, MSUlab v0.5.2, PicVideo JPEG v.2.10.0.29, VBLE beta 2007 : Alpary, ArithYuv, AVIzlib, CamStudio GZIP, CorePNG, FastCodec, FFV1, Huffyuv, Lagarith, LOCO, LZO, MSU Lab, PICVideo, Snow, x264, YULS	in 2007 – more detailed report with new codecs including first standard H.264
MSU MPEG-4 codecs comparison	Objective comparison of MPEG-4 codecs	2005 Mar.	DivX 5.2.1, DivX 4.12, DivX 3.22, MS MPEG-4 3688 v3, XviD 1.0.3, 3ivx D4 4.5.1, OpenDivX 0.3	Different versions of DivX were also compared. The Xvid results may be erroneous, as deblocking was disabled for it while used for DivX.
Subjective Comparison of Modern Video Codecs	Scientifically accurate subjective comparison using 50 experts and SAMVIQ methodology	2006 Feb.	DivX 6.0, Xvid 1.1.0, x264, WMV 9.0	PSNR via VQM via SSIM comparison was also done
MPEG-2 Video Decoders Comparison	Objective MPEG-2 Decoders comparison	2006 May.	bitcontrol MPEG-2 Video Decoder, DScaler MPEG2 Video Decoder, Elecard MPEG-2 Video Decoder, ffdshow MPEG-4 Video Decoder, InterVideo Video Decoder, Ligos MPEG Video Decoder, MainConcept MPEG Video Decoder, Pinnacle MPEG-2 Decoder	Objectly tested decoders "crash test"
Codecs comparison	Personal subjective opinion	2003 Nov.	3ivx, Avid AVI 2.02, Cinepak, DivX 3.11, DivX 4.12, DivX 5.0.2, DV, Huffyuv, Indeo 3.2, Indeo 4.4, Indeo 5.10, Microsoft MPEG-4 v1, Microsoft MPEG-4 v2, Microsoft RLE, Microsoft Video 1, XviD, 3ivx, Animation, Blackmagic 10-bit, Blackmagic 8-bit, Cinepak, DV, H.261, H.263, Motion-JPEG, MPEG-4 Video, PNG, Sorenson Video, Sorenson Video 3	Sometimes comparison is short
Evaluation of Dirac and Theora	Scientific paper	2009 Mar.	Dirac, Dirac Pro, Theora I, H.264, Motion JPEG2000	Quite detailed comparison of software available in Q2-2008; However, a buggy version of ffmpeg2Theora was used
VP8 versus x264	Objective and subjective quality comparison of VP8 and x264	2010 Jun.	VP8, x264	VQM, SSIM and PSNR for 19 CIF video clips with bitrates of 100, 200, 500 and 1000 kbit/s