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Internet Engineering Task Force (IETF) A. Filippov
Request for Comments: 8761 Huawei Technologies
Category: Informational A. Norkin
ISSN: 2070-1721 Netflix
J.R. Alvarez
Huawei Technologies
April 2020
Video Codec Requirements and Evaluation Methodology
Abstract
This document provides requirements for a video codec designed mainly
for use over the Internet. In addition, this document describes an
evaluation methodology for measuring the compression efficiency to
determine whether or not the stated requirements have been fulfilled.
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Engineering Task Force
(IETF). It represents the consensus of the IETF community. It has
received public review and has been approved for publication by the
Internet Engineering Steering Group (IESG). Not all documents
approved by the IESG are candidates for any level of Internet
Standard; see Section 2 of RFC 7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
https://www.rfc-editor.org/info/rfc8761.
Copyright Notice
Copyright (c) 2020 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
(https://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
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to this document. Code Components extracted from this document must
include Simplified BSD License text as described in Section 4.e of
the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. Introduction
2. Terminology Used in This Document
2.1. Definitions
2.2. Abbreviations
3. Applications
3.1. Internet Video Streaming
3.2. Internet Protocol Television (IPTV)
3.3. Video Conferencing
3.4. Video Sharing
3.5. Screencasting
3.6. Game Streaming
3.7. Video Monitoring and Surveillance
4. Requirements
4.1. General Requirements
4.1.1. Coding Efficiency
4.1.2. Profiles and Levels
4.1.3. Bitstream Syntax
4.1.4. Parsing and Identification of Sample Components
4.1.5. Perceptual Quality Tools
4.1.6. Buffer Model
4.1.7. Integration
4.2. Basic Requirements
4.2.1. Input Source Formats
4.2.2. Coding Delay
4.2.3. Complexity
4.2.4. Scalability
4.2.5. Error Resilience
4.3. Optional Requirements
4.3.1. Input Source Formats
4.3.2. Scalability
4.3.3. Complexity
4.3.4. Coding Efficiency
5. Evaluation Methodology
6. Security Considerations
7. IANA Considerations
8. References
8.1. Normative References
8.2. Informative References
Acknowledgments
Authors' Addresses
1. Introduction
This document presents the requirements for a video codec designed
mainly for use over the Internet. The requirements encompass a wide
range of applications that use data transmission over the Internet,
including Internet video streaming, IPTV, peer-to-peer video
conferencing, video sharing, screencasting, game streaming, and video
monitoring and surveillance. For each application, typical
resolutions, frame rates, and picture-access modes are presented.
Specific requirements related to data transmission over packet-loss
networks are considered as well. In this document, when we discuss
data-protection techniques, we only refer to methods designed and
implemented to protect data inside the video codec since there are
many existing techniques that protect generic data transmitted over
networks with packet losses. From the theoretical point of view,
both packet-loss and bit-error robustness can be beneficial for video
codecs. In practice, packet losses are a more significant problem
than bit corruption in IP networks. It is worth noting that there is
an evident interdependence between the possible amount of delay and
the necessity of error-robust video streams:
* If the amount of delay is not crucial for an application, then
reliable transport protocols such as TCP that retransmit
undelivered packets can be used to guarantee correct decoding of
transmitted data.
* If the amount of delay must be kept low, then either data
transmission should be error free (e.g., by using managed
networks) or the compressed video stream should be error
resilient.
Thus, error resilience can be useful for delay-critical applications
to provide low delay in a packet-loss environment.
2. Terminology Used in This Document
2.1. Definitions
High dynamic range imaging
A set of techniques that allows a greater dynamic range of
exposures or values (i.e., a wider range of values between light
and dark areas) than normal digital imaging techniques. The
intention is to accurately represent the wide range of intensity
levels found in examples such as exterior scenes that include
light-colored items struck by direct sunlight and areas of deep
shadow [7].
Random access period
The period of time between the two closest independently decodable
frames (pictures).
RD-point
A point in a two-dimensional rate-distortion space where the
values of bitrate and quality metric are used as x- and
y-coordinates, respectively.
Visually lossless compression
A form or manner of lossy compression where the data that are lost
after the file is compressed and decompressed is not detectable to
the eye; the compressed data appear identical to the uncompressed
data [8].
Wide color gamut
A certain complete color subset (e.g., considered in ITU-R BT.2020
[1]) that supports a wider range of colors (i.e., an extended
range of colors that can be generated by a specific input or
output device such as a video camera, monitor, or printer and can
be interpreted by a color model) than conventional color gamuts
(e.g., considered in ITU-R BT.601 [17] or BT.709 [20]).
2.2. Abbreviations
AI All-Intra (each picture is intra-coded)
BD-Rate Bjontegaard Delta Rate
FIZD just the First picture is Intra-coded, Zero structural
Delay
FPS Frames per Second
GOP Group of Picture
GPU Graphics Processing Unit
HBR High Bitrate Range
HDR High Dynamic Range
HRD Hypothetical Reference Decoder
HEVC High Efficiency Video Coding
IPTV Internet Protocol Television
LBR Low Bitrate Range
MBR Medium Bitrate Range
MOS Mean Opinion Score
MS-SSIM Multi-Scale Structural Similarity quality index
PAM Picture Access Mode
PSNR Peak Signal-to-Noise Ratio
QoS Quality of Service
QP Quantization Parameter
RA Random Access
RAP Random Access Period
RD Rate-Distortion
SEI Supplemental Enhancement Information
SIMD Single Instruction, Multiple Data
SNR Signal-to-Noise Ratio
UGC User-Generated Content
VDI Virtual Desktop Infrastructure
VUI Video Usability Information
WCG Wide Color Gamut
3. Applications
In this section, an overview of video codec applications that are
currently available on the Internet market is presented. It is worth
noting that there are different use cases for each application that
define a target platform; hence, there are different types of
communication channels involved (e.g., wired or wireless channels)
that are characterized by different QoS as well as bandwidth; for
instance, wired channels are considerably more free from error than
wireless channels and therefore require different QoS approaches.
The target platform, the channel bandwidth, and the channel quality
determine resolutions, frame rates, and either quality or bitrates
for video streams to be encoded or decoded. By default, color format
YCbCr 4:2:0 is assumed for the application scenarios listed below.
3.1. Internet Video Streaming
Typical content for this application is movies, TV series and shows,
and animation. Internet video streaming uses a variety of client
devices and has to operate under changing network conditions. For
this reason, an adaptive streaming model has been widely adopted.
Video material is encoded at different quality levels and different
resolutions, which are then chosen by a client depending on its
capabilities and current network bandwidth. An example combination
of resolutions and bitrates is shown in Table 1.
A video encoding pipeline in on-demand Internet video streaming
typically operates as follows:
* Video is encoded in the cloud by software encoders.
* Source video is split into chunks, each of which is encoded
separately, in parallel.
* Closed-GOP encoding with intrapicture intervals of 2-5 seconds (or
longer) is used.
* Encoding is perceptually optimized. Perceptual quality is
important and should be considered during the codec development.
+------------+-----+------------------------------------------------+
| Resolution | PAM | Frame Rate, FPS ** |
| * | | |
+============+=====+================================================+
| 4K, | RA | 24/1.001, 24, 25, |
| 3840x2160 | | 30/1.001, 30, 50, |
+------------+-----+ 60/1.001, 60, 100, |
| 2K | RA | 120/1.001, 120 |
| (1080p), | | |
| 1920x1080 | | |
+------------+-----+ |
| 1080i, | RA | |
| 1920x1080* | | |
+------------+-----+ |
| 720p, | RA | |
| 1280x720 | | |
+------------+-----+ |
| 576p | RA | |
| (EDTV), | | |
| 720x576 | | |
+------------+-----+ |
| 576i | RA | |
| (SDTV), | | |
| 720x576* | | |
+------------+-----+ |
| 480p | RA | |
| (EDTV), | | |
| 720x480 | | |
+------------+-----+ |
| 480i | RA | |
| (SDTV), | | |
| 720x480* | | |
+------------+-----+ |
| 512x384 | RA | |
+------------+-----+ |
| QVGA, | RA | |
| 320x240 | | |
+------------+-----+------------------------------------------------+
Table 1: Internet Video Streaming: Typical Values of Resolutions,
Frame Rates, and PAMs
*Note: Interlaced content can be handled at the higher system level
and not necessarily by using specialized video coding tools. It is
included in this table only for the sake of completeness, as most
video content today is in the progressive format.
**Note: The set of frame rates presented in this table is taken from
Table 2 in [1].
The characteristics and requirements of this application scenario are
as follows:
* High encoder complexity (up to 10x and more) can be tolerated
since encoding happens once and in parallel for different
segments.
* Decoding complexity should be kept at reasonable levels to enable
efficient decoder implementation.
* Support and efficient encoding of a wide range of content types
and formats is required:
- High Dynamic Range (HDR), Wide Color Gamut (WCG), high-
resolution (currently, up to 4K), and high-frame-rate content
are important use cases; the codec should be able to encode
such content efficiently.
- Improvement of coding efficiency at both lower and higher
resolutions is important since low resolutions are used when
streaming in low-bandwidth conditions.
- Improvement on both "easy" and "difficult" content in terms of
compression efficiency at the same quality level contributes to
the overall bitrate/storage savings.
- Film grain (and sometimes other types of noise) is often
present in movies and similar content; this is usually part of
the creative intent.
* Significant improvements in compression efficiency between
generations of video standards are desirable since this scenario
typically assumes long-term support of legacy video codecs.
* Random access points are inserted frequently (one per 2-5 seconds)
to enable switching between resolutions and fast-forward playback.
* The elementary stream should have a model that allows easy parsing
and identification of the sample components.
* Middle QP values are normally used in streaming; this is also the
range where compression efficiency is important for this scenario.
* Scalability or other forms of supporting multiple quality
representations are beneficial if they do not incur significant
bitrate overhead and if mandated in the first version.
3.2. Internet Protocol Television (IPTV)
This is a service for delivering television content over IP-based
networks. IPTV may be classified into two main groups based on the
type of delivery, as follows:
* unicast (e.g., for video on demand), where delay is not crucial;
and
* multicast/broadcast (e.g., for transmitting news) where zapping
(i.e., stream changing) delay is important.
In the IPTV scenario, traffic is transmitted over managed (QoS-based)
networks. Typical content used in this application is news, movies,
cartoons, series, TV shows, etc. One important requirement for both
groups is that random access to pictures (i.e., the random access
period (RAP)) should be kept small enough (approximately 1-5
seconds). Optional requirements are as follows:
* Temporal (frame-rate) scalability; and
* Resolution and quality (SNR) scalability.
For this application, typical values of resolutions, frame rates, and
PAMs are presented in Table 2.
+------------+-----+------------------------------------------------+
| Resolution | PAM | Frame Rate, FPS ** |
| * | | |
+============+=====+================================================+
| 2160p | RA | 24/1.001, 24, 25, |
| (4K), | | 30/1.001, 30, 50, |
| 3840x2160 | | 60/1.001, 60, 100, |
+------------+-----+ 120/1.001, 120 |
| 1080p, | RA | |
| 1920x1080 | | |
+------------+-----+ |
| 1080i, | RA | |
| 1920x1080* | | |
+------------+-----+ |
| 720p, | RA | |
| 1280x720 | | |
+------------+-----+ |
| 576p | RA | |
| (EDTV), | | |
| 720x576 | | |
+------------+-----+ |
| 576i | RA | |
| (SDTV), | | |
| 720x576* | | |
+------------+-----+ |
| 480p | RA | |
| (EDTV), | | |
| 720x480 | | |
+------------+-----+ |
| 480i | RA | |
| (SDTV), | | |
| 720x480* | | |
+------------+-----+------------------------------------------------+
Table 2: IPTV: Typical Values of Resolutions, Frame Rates, and PAMs
*Note: Interlaced content can be handled at the higher system level
and not necessarily by using specialized video coding tools. It is
included in this table only for the sake of completeness, as most
video content today is in a progressive format.
**Note: The set of frame rates presented in this table is taken from
Table 2 in [1].
3.3. Video Conferencing
This is a form of video connection over the Internet. This form
allows users to establish connections to two or more people by two-
way video and audio transmission for communication in real time. For
this application, both stationary and mobile devices can be used.
The main requirements are as follows:
* Delay should be kept as low as possible (the preferable and
maximum end-to-end delay values should be less than 100 ms [9] and
320 ms [2], respectively);
* Temporal (frame-rate) scalability; and
* Error robustness.
Support of resolution and quality (SNR) scalability is highly
desirable. For this application, typical values of resolutions,
frame rates, and PAMs are presented in Table 3.
+------------------+-----------------+------+
| Resolution | Frame Rate, FPS | PAM |
+==================+=================+======+
| 1080p, 1920x1080 | 15, 30 | FIZD |
+------------------+-----------------+------+
| 720p, 1280x720 | 30, 60 | FIZD |
+------------------+-----------------+------+
| 4CIF, 704x576 | 30, 60 | FIZD |
+------------------+-----------------+------+
| 4SIF, 704x480 | 30, 60 | FIZD |
+------------------+-----------------+------+
| VGA, 640x480 | 30, 60 | FIZD |
+------------------+-----------------+------+
| 360p, 640x360 | 30, 60 | FIZD |
+------------------+-----------------+------+
Table 3: Video Conferencing: Typical
Values of Resolutions, Frame Rates, and
PAMs
3.4. Video Sharing
This is a service that allows people to upload and share video data
(using live streaming or not) and watch those videos. It is also
known as video hosting. A typical User-Generated Content (UGC)
scenario for this application is to capture video using mobile
cameras such as GoPros or cameras integrated into smartphones
(amateur video). The main requirements are as follows:
* Random access to pictures for downloaded video data;
* Temporal (frame-rate) scalability; and
* Error robustness.
Support of resolution and quality (SNR) scalability is highly
desirable. For this application, typical values of resolutions,
frame rates, and PAMs are presented in Table 4.
Typical values of resolutions and frame rates in Table 4 are taken
from [10].
+-----------------------+------------------------+-----+
| Resolution | Frame Rate, FPS | PAM |
+=======================+========================+=====+
| 2160p (4K), 3840x2160 | 24, 25, 30, 48, 50, 60 | RA |
+-----------------------+------------------------+-----+
| 1440p (2K), 2560x1440 | 24, 25, 30, 48, 50, 60 | RA |
+-----------------------+------------------------+-----+
| 1080p, 1920x1080 | 24, 25, 30, 48, 50, 60 | RA |
+-----------------------+------------------------+-----+
| 720p, 1280x720 | 24, 25, 30, 48, 50, 60 | RA |
+-----------------------+------------------------+-----+
| 480p, 854x480 | 24, 25, 30, 48, 50, 60 | RA |
+-----------------------+------------------------+-----+
| 360p, 640x360 | 24, 25, 30, 48, 50, 60 | RA |
+-----------------------+------------------------+-----+
Table 4: Video Sharing: Typical Values of
Resolutions, Frame Rates, and PAMs
3.5. Screencasting
This is a service that allows users to record and distribute video
data from a computer screen. This service requires efficient
compression of computer-generated content with high visual quality up
to visually and mathematically (numerically) lossless [11].
Currently, this application includes business presentations
(PowerPoint, Word documents, email messages, etc.), animation
(cartoons), gaming content, and data visualization. This type of
content is characterized by fast motion, rotation, smooth shade, 3D
effect, highly saturated colors with full resolution, clear textures
and sharp edges with distinct colors [11], virtual desktop
infrastructure (VDI), screen/desktop sharing and collaboration,
supervisory control and data acquisition (SCADA) display, automotive/
navigation display, cloud gaming, factory automation display,
wireless display, display wall, digital operating room (DiOR), etc.
For this application, an important requirement is the support of low-
delay configurations with zero structural delay for a wide range of
video formats (e.g., RGB) in addition to YCbCr 4:2:0 and YCbCr 4:4:4
[11]. For this application, typical values of resolutions, frame
rates, and PAMs are presented in Table 5.
+-----------------------+-----------------+--------------+
| Resolution | Frame Rate, FPS | PAM |
+=======================+=================+==============+
| Input color format: RGB 4:4:4 |
+-----------------------+-----------------+--------------+
| 5k, 5120x2880 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| 4k, 3840x2160 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| WQXGA, 2560x1600 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| WUXGA, 1920x1200 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| WSXGA+, 1680x1050 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| WXGA, 1280x800 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| XGA, 1024x768 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| SVGA, 800x600 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| VGA, 640x480 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| Input color format: YCbCr 4:4:4 |
+-----------------------+-----------------+--------------+
| 5k, 5120x2880 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| 4k, 3840x2160 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| 1440p (2K), 2560x1440 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| 1080p, 1920x1080 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
| 720p, 1280x720 | 15, 30, 60 | AI, RA, FIZD |
+-----------------------+-----------------+--------------+
Table 5: Screencasting for RGB and YCbCr 4:4:4 Format:
Typical Values of Resolutions, Frame Rates, and PAMs
3.6. Game Streaming
This is a service that provides game content over the Internet to
different local devices such as notebooks and gaming tablets. In
this category of applications, the server renders 3D games in a cloud
server and streams the game to any device with a wired or wireless
broadband connection [12]. There are low-latency requirements for
transmitting user interactions and receiving game data with a
turnaround delay of less than 100 ms. This allows anyone to play (or
resume) full-featured games from anywhere on the Internet [12]. An
example of this application is Nvidia Grid [12]. Another application
scenario of this category is broadcast of video games played by
people over the Internet in real time or for later viewing [12].
There are many companies, such as Twitch and YY in China, that enable
game broadcasting [12]. Games typically contain a lot of sharp edges
and large motion [12]. The main requirements are as follows:
* Random access to pictures for game broadcasting;
* Temporal (frame-rate) scalability; and
* Error robustness.
Support of resolution and quality (SNR) scalability is highly
desirable. For this application, typical values of resolutions,
frame rates, and PAMs are similar to ones presented in Table 3.
3.7. Video Monitoring and Surveillance
This is a type of live broadcasting over IP-based networks. Video
streams are sent to many receivers at the same time. A new receiver
may connect to the stream at an arbitrary moment, so the random
access period should be kept small enough (approximately, 1-5
seconds). Data are transmitted publicly in the case of video
monitoring and privately in the case of video surveillance. For IP
cameras that have to capture, process, and encode video data,
complexity -- including computational and hardware complexity, as
well as memory bandwidth -- should be kept low to allow real-time
processing. In addition, support of a high dynamic range and a
monochrome mode (e.g., for infrared cameras) as well as resolution
and quality (SNR) scalability is an essential requirement for video
surveillance. In some use cases, high video signal fidelity is
required even after lossy compression. Typical values of
resolutions, frame rates, and PAMs for video monitoring and
surveillance applications are presented in Table 6.
+-----------------------+-----------------+----------+
| Resolution | Frame Rate, FPS | PAM |
+=======================+=================+==========+
| 2160p (4K), 3840x2160 | 12, 25, 30 | RA, FIZD |
+-----------------------+-----------------+----------+
| 5Mpixels, 2560x1920 | 12, 25, 30 | RA, FIZD |
+-----------------------+-----------------+----------+
| 1080p, 1920x1080 | 25, 30 | RA, FIZD |
+-----------------------+-----------------+----------+
| 1.23Mpixels, 1280x960 | 25, 30 | RA, FIZD |
+-----------------------+-----------------+----------+
| 720p, 1280x720 | 25, 30 | RA, FIZD |
+-----------------------+-----------------+----------+
| SVGA, 800x600 | 25, 30 | RA, FIZD |
+-----------------------+-----------------+----------+
Table 6: Video Monitoring and Surveillance:
Typical Values of Resolutions, Frame Rates, and
PAMs
4. Requirements
Taking the requirements discussed above for specific video
applications, this section proposes requirements for an Internet
video codec.
4.1. General Requirements
4.1.1. Coding Efficiency
The most fundamental requirement is coding efficiency, i.e.,
compression performance on both "easy" and "difficult" content for
applications and use cases in Section 3. The codec should provide
higher coding efficiency over state-of-the-art video codecs such as
HEVC/H.265 and VP9, at least 25%, in accordance with the methodology
described in Section 5 of this document. For higher resolutions, the
improvements in coding efficiency are expected to be higher than for
lower resolutions.
4.1.2. Profiles and Levels
Good-quality specification and well-defined profiles and levels are
required to enable device interoperability and facilitate decoder
implementations. A profile consists of a subset of entire bitstream
syntax elements; consequently, it also defines the necessary tools
for decoding a conforming bitstream of that profile. A level imposes
a set of numerical limits to the values of some syntax elements. An
example of codec levels to be supported is presented in Table 7. An
actual level definition should include constraints on features that
impact the decoder complexity. For example, these features might be
as follows: maximum bitrate, line buffer size, memory usage, etc.
+-------+-----------------------------------------------------------+
| Level | Example picture resolution at highest frame rate |
+=======+===========================================================+
| 1 | 128x96(12,288*)@30.0 |
| | 176x144(25,344*)@15.0 |
+-------+-----------------------------------------------------------+
| 2 | 352x288(101,376*)@30.0 |
+-------+-----------------------------------------------------------+
| 3 | 352x288(101,376*)@60.0 |
| | 640x360(230,400*)@30.0 |
+-------+-----------------------------------------------------------+
| 4 | 640x360(230,400*)@60.0 |
| | 960x540(518,400*)@30.0 |
+-------+-----------------------------------------------------------+
| 5 | 720x576(414,720*)@75.0 |
| | 960x540(518,400*)@60.0 |
| | 1280x720(921,600*)@30.0 |
+-------+-----------------------------------------------------------+
| 6 | 1,280x720(921,600*)@68.0 |
| | 2,048x1,080(2,211,840*)@30.0 |
+-------+-----------------------------------------------------------+
| 7 | 1,280x720(921,600*)@120.0 |
+-------+-----------------------------------------------------------+
| 8 | 1,920x1,080(2,073,600*)@120.0 |
| | 3,840x2,160(8,294,400*)@30.0 |
| | 4,096x2,160(8,847,360*)@30.0 |
+-------+-----------------------------------------------------------+
| 9 | 1,920x1,080(2,073,600*)@250.0 |
| | 4,096x2,160(8,847,360*)@60.0 |
+-------+-----------------------------------------------------------+
| 10 | 1,920x1,080(2,073,600*)@300.0 |
| | 4,096x2,160(8,847,360*)@120.0 |
+-------+-----------------------------------------------------------+
| 11 | 3,840x2,160(8,294,400*)@120.0 |
| | 8,192x4,320(35,389,440*)@30.0 |
+-------+-----------------------------------------------------------+
| 12 | 3,840x2,160(8,294,400*)@250.0 |
| | 8,192x4,320(35,389,440*)@60.0 |
+-------+-----------------------------------------------------------+
| 13 | 3,840x2,160(8,294,400*)@300.0 |
| | 8,192x4,320(35,389,440*)@120.0 |
+-------+-----------------------------------------------------------+
Table 7: Codec Levels
*Note: The quantities of pixels are presented for applications in
which a picture can have an arbitrary size (e.g., screencasting).
4.1.3. Bitstream Syntax
Bitstream syntax should allow extensibility and backward
compatibility. New features can be supported easily by using
metadata (such as SEI messages, VUI, and headers) without affecting
the bitstream compatibility with legacy decoders. A newer version of
the decoder shall be able to play bitstreams of an older version of
the same or lower profile and level.
4.1.4. Parsing and Identification of Sample Components
A bitstream should have a model that allows easy parsing and
identification of the sample components (such as Annex B of ISO/IEC
14496-10 [18] or ISO/IEC 14496-15 [19]). In particular, information
needed for packet handling (e.g., frame type) should not require
parsing anything below the header level.
4.1.5. Perceptual Quality Tools
Perceptual quality tools (such as adaptive QP and quantization
matrices) should be supported by the codec bitstream.
4.1.6. Buffer Model
The codec specification shall define a buffer model such as
hypothetical reference decoder (HRD).
4.1.7. Integration
Specifications providing integration with system and delivery layers
should be developed.
4.2. Basic Requirements
4.2.1. Input Source Formats
Input pictures coded by a video codec should have one of the
following formats:
* Bit depth: 8 and 10 bits (up to 12 bits for a high profile) per
color component.
* Color sampling formats:
- YCbCr 4:2:0
- YCbCr 4:4:4, YCbCr 4:2:2, and YCbCr 4:0:0 (preferably in
different profile(s))
* For profiles with bit depth of 10 bits per sample or higher,
support of high dynamic range and wide color gamut.
* Support of arbitrary resolution according to the level constraints
for applications in which a picture can have an arbitrary size
(e.g., in screencasting).
Exemplary input source formats for codec profiles are shown in
Table 8.
+---------+--------------------------------+------------------------+
| Profile | Bit depths per color component | Color sampling |
| | | formats |
+=========+================================+========================+
| 1 | 8 and 10 | 4:0:0 and 4:2:0 |
+---------+--------------------------------+------------------------+
| 2 | 8 and 10 | 4:0:0, 4:2:0, |
| | | and 4:4:4 |
+---------+--------------------------------+------------------------+
| 3 | 8, 10, and 12 | 4:0:0, 4:2:0, |
| | | 4:2:2, and 4:4:4 |
+---------+--------------------------------+------------------------+
Table 8: Exemplary Input Source Formats for Codec Profiles
4.2.2. Coding Delay
In order to meet coding delay requirements, a video codec should
support all of the following:
* Support of configurations with zero structural delay, also
referred to as "low-delay" configurations.
- Note: End-to-end delay should be no more than 320 ms [2], but
it is preferable for its value to be less than 100 ms [9].
* Support of efficient random access point encoding (such as
intracoding and resetting of context variables), as well as
efficient switching between multiple quality representations.
* Support of configurations with nonzero structural delay (such as
out-of-order or multipass encoding) for applications without low-
delay requirements, if such configurations provide additional
compression efficiency improvements.
4.2.3. Complexity
Encoding and decoding complexity considerations are as follows:
* Feasible real-time implementation of both an encoder and a decoder
supporting a chosen subset of tools for hardware and software
implementation on a wide range of state-of-the-art platforms. The
subset of real-time encoder tools should provide meaningful
improvement in compression efficiency at reasonable complexity of
hardware and software encoder implementations as compared to real-
time implementations of state-of-the-art video compression
technologies such as HEVC/H.265 and VP9.
* High-complexity software encoder implementations used by offline
encoding applications can have a 10x or more complexity increase
compared to state-of-the-art video compression technologies such
as HEVC/H.265 and VP9.
4.2.4. Scalability
The mandatory scalability requirement is as follows:
* Temporal (frame-rate) scalability should be supported.
4.2.5. Error Resilience
In order to meet the error resilience requirement, a video codec
should satisfy all of the following conditions:
* Tools that are complementary to the error-protection mechanisms
implemented on the transport level should be supported.
* The codec should support mechanisms that facilitate packetization
of a bitstream for common network protocols.
* Packetization mechanisms should enable frame-level error recovery
by means of retransmission or error concealment.
* The codec should support effective mechanisms for allowing
decoding and reconstruction of significant parts of pictures in
the event that parts of the picture data are lost in transmission.
* The bitstream specification shall support independently decodable
subframe units similar to slices or independent tiles. It shall
be possible for the encoder to restrict the bitstream to allow
parsing of the bitstream after a packet loss and to communicate it
to the decoder.
4.3. Optional Requirements
4.3.1. Input Source Formats
It is a desired but not mandatory requirement for a video codec to
support some of the following features:
* Bit depth: up to 16 bits per color component.
* Color sampling formats: RGB 4:4:4.
* Auxiliary channel (e.g., alpha channel) support.
4.3.2. Scalability
Desirable scalability requirements are as follows:
* Resolution and quality (SNR) scalability that provides a low-
compression efficiency penalty (increase of up to 5% of BD-rate
[13] per layer with reasonable increase of both computational and
hardware complexity) can be supported in the main profile of the
codec being developed by the NETVC Working Group. Otherwise, a
separate profile is needed to support these types of scalability.
* Computational complexity scalability (i.e., computational
complexity is decreasing along with degrading picture quality) is
desirable.
4.3.3. Complexity
Tools that enable parallel processing (e.g., slices, tiles, and wave-
front propagation processing) at both encoder and decoder sides are
highly desirable for many applications.
* High-level multicore parallelism: encoder and decoder operation,
especially entropy encoding and decoding, should allow multiple
frames or subframe regions (e.g., 1D slices, 2D tiles, or
partitions) to be processed concurrently, either independently or
with deterministic dependencies that can be efficiently pipelined.
* Low-level instruction-set parallelism: favor algorithms that are
SIMD/GPU friendly over inherently serial algorithms
4.3.4. Coding Efficiency
Compression efficiency on noisy content, content with film grain,
computer generated content, and low resolution materials is
desirable.
5. Evaluation Methodology
As shown in Figure 1, compression performance testing is performed in
three overlapped ranges that encompass ten different bitrate values:
* Low bitrate range (LBR) is the range that contains the four lowest
bitrates of the ten specified bitrates (one of the four bitrate
values is shared with the neighboring range).
* Medium bitrate range (MBR) is the range that contains the four
medium bitrates of the ten specified bitrates (two of the four
bitrate values are shared with the neighboring ranges).
* High bitrate range (HBR) is the range that contains the four
highest bitrates of the ten specified bitrates (one of the four
bitrate values is shared with the neighboring range).
Initially, for the codec selected as a reference one (e.g., HEVC or
VP9), a set of ten QP (quantization parameter) values should be
specified as in [14], and corresponding quality values should be
calculated. In Figure 1, QP and quality values are denoted as
"QP0"-"QP9" and "Q0"-"Q9", respectively. To guarantee the overlaps
of quality levels between the bitrate ranges of the reference and
tested codecs, a quality alignment procedure should be performed for
each range's outermost (left- and rightmost) quality levels Qk of the
reference codec (i.e., for Q0, Q3, Q6, and Q9) and the quality levels
Q'k (i.e., Q'0, Q'3, Q'6, and Q'9) of the tested codec. Thus, these
quality levels Q'k, and hence the corresponding QP value QP'k (i.e.,
QP'0, QP'3, QP'6, and QP'9), of the tested codec should be selected
using the following formulas:
Q'k = min { abs(Q'i - Qk) },
i in R
QP'k = argmin { abs(Q'i(QP'i) - Qk(QPk)) },
i in R
where R is the range of the QP indexes of the tested codec, i.e., the
candidate Internet video codec. The inner quality levels (i.e., Q'1,
Q'2, Q'4, Q'5, Q'7, and Q'8), as well as their corresponding QP
values of each range (i.e., QP'1, QP'2, QP'4, QP'5, QP'7, and QP'8),
should be as equidistantly spaced as possible between the left- and
rightmost quality levels without explicitly mapping their values
using the procedure described above.
QP'9 QP'8 QP'7 QP'6 QP'5 QP'4 QP'3 QP'2 QP'1 QP'0 <+-----
^ ^ ^ ^ ^ ^ ^ ^ ^ ^ | Tested
| | | | | | | | | | | codec
Q'0 Q'1 Q'2 Q'3 Q'4 Q'5 Q'6 Q'7 Q'8 Q'9 <+-----
^ ^ ^ ^
| | | |
Q0 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 <+-----
^ ^ ^ ^ ^ ^ ^ ^ ^ ^ | Reference
| | | | | | | | | | | codec
QP9 QP8 QP7 QP6 QP5 QP4 QP3 QP2 QP1 QP0 <+-----
+----------------+--------------+--------------+--------->
^ ^ ^ ^ Bitrate
|-------LBR------| |-----HBR------|
^ ^
|------MBR-----|
Figure 1: Quality/QP Alignment for Compression Performance Evaluation
Since the QP mapping results may vary for different sequences, this
quality alignment procedure eventually needs to be performed
separately for each quality assessment index and each sequence used
for codec performance evaluation to fulfill the requirements
described above.
To assess the quality of output (decoded) sequences, two indexes
(PSNR [3] and MS-SSIM [3] [15]) are separately computed. In the case
of the YCbCr color format, PSNR should be calculated for each color
plane, whereas MS-SSIM is calculated for the luma channel only. In
the case of the RGB color format, both metrics are computed for R, G,
and B channels. Thus, for each sequence, 30 RD-points for PSNR
(i.e., three RD-curves, one for each channel) and 10 RD-points for
MS-SSIM (i.e., one RD-curve, for luma channel only) should be
calculated in the case of YCbCr. If content is encoded as RGB, 60
RD-points (30 for PSNR and 30 for MS-SSIM) should be calculated
(i.e., three RD-curves, one for each channel) are computed for PSNR
as well as three RD-curves (one for each channel) for MS-SSIM.
Finally, to obtain an integral estimation, BD-rate savings [13]
should be computed for each range and each quality index. In
addition, average values over all three ranges should be provided for
both PSNR and MS-SSIM. A list of video sequences that should be used
for testing, as well as the ten QP values for the reference codec,
are defined in [14]. Testing processes should use the information on
the codec applications presented in this document. As the reference
for evaluation, state-of-the-art video codecs such as HEVC/H.265
[4][5] or VP9 must be used. The reference source code of the HEVC/
H.265 codec can be found at [6]. The HEVC/H.265 codec must be
configured according to [16] and Table 9.
+----------------------+--------------------------------------------+
| Intra-period, second | HEVC/H.265 encoding |
| | mode according to [16] |
+======================+============================================+
| AI | Intra Main or Intra |
| | Main10 |
+----------------------+--------------------------------------------+
| RA | Random access Main or |
| | Random access Main10 |
+----------------------+--------------------------------------------+
| FIZD | Low delay Main or |
| | Low delay Main10 |
+----------------------+--------------------------------------------+
Table 9: Intraperiods for Different HEVC/H.265 Encoding Modes
According to [16]
According to the coding efficiency requirement described in
Section 4.1.1, BD-rate savings calculated for each color plane and
averaged for all the video sequences used to test the NETVC codec
should be, at least,
* 25% if calculated over the whole bitrate range; and
* 15% if calculated for each bitrate subrange (LBR, MBR, HBR).
Since values of the two objective metrics (PSNR and MS-SSIM) are
available for some color planes, each value should meet these coding
efficiency requirements. That is, the final BD-rate saving denoted
as S is calculated for a given color plane as follows:
S = min { S_psnr, S_ms-ssim }
where S_psnr and S_ms-ssim are BD-rate savings calculated for the
given color plane using PSNR and MS-SSIM metrics, respectively.
In addition to the objective quality measures defined above,
subjective evaluation must also be performed for the final NETVC
codec adoption. For subjective tests, the MOS-based evaluation
procedure must be used as described in Section 2.1 of [3]. For
perception-oriented tools that primarily impact subjective quality,
additional tests may also be individually assigned even for
intermediate evaluation, subject to a decision of the NETVC WG.
6. Security Considerations
This document itself does not address any security considerations.
However, it is worth noting that a codec implementation (for both an
encoder and a decoder) should take into consideration the worst-case
computational complexity, memory bandwidth, and physical memory size
needed to process the potentially untrusted input (e.g., the decoded
pictures used as references).
7. IANA Considerations
This document has no IANA actions.
8. References
8.1. Normative References
[1] ITU-R, "Parameter values for ultra-high definition
television systems for production and international
programme exchange", ITU-R Recommendation BT.2020-2,
October 2015,
<https://www.itu.int/rec/R-REC-BT.2020-2-201510-I/en>.
[2] ITU-T, "Quality of Experience requirements for
telepresence services", ITU-T Recommendation G.1091,
October 2014, <https://www.itu.int/rec/T-REC-G.1091/en>.
[3] ISO, "Information technology -- Advanced image coding and
evaluation -- Part 1: Guidelines for image coding system
evaluation", ISO/IEC TR 29170-1:2017, October 2017,
<https://www.iso.org/standard/63637.html>.
[4] ISO, "Information technology -- High efficiency coding and
media delivery in heterogeneous environments -- Part 2:
High efficiency video coding", ISO/IEC 23008-2:2015, May
2018, <https://www.iso.org/standard/67660.html>.
[5] ITU-T, "High efficiency video coding", ITU-T
Recommendation H.265, November 2019,
<https://www.itu.int/rec/T-REC-H.265>.
[6] Fraunhofer Institute for Telecommunications, "High
Efficiency Video Coding (HEVC) reference software (HEVC
Test Model also known as HM)",
<https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/>.
8.2. Informative References
[7] Federal Agencies Digital Guidelines Initiative, "Term:
High dynamic range imaging",
<http://www.digitizationguidelines.gov/
term.php?term=highdynamicrangeimaging>.
[8] Federal Agencies Digital Guidelines Initiative, "Term:
Compression, visually lossless",
<http://www.digitizationguidelines.gov/
term.php?term=compressionvisuallylossless>.
[9] Wenger, S., "The case for scalability support in version 1
of Future Video Coding", SG 16 (Study Period
2013) Contribution 988, September 2015,
<https://www.itu.int/md/T13-SG16-C-0988/en>.
[10] YouTube, "Recommended upload encoding settings",
<https://support.google.com/youtube/answer/1722171?hl=en>.
[11] Yu, H., Ed., McCann, K., Ed., Cohen, R., Ed., and P. Amon,
Ed., "Requirements for an extension of HEVC for coding of
screen content", ISO/IEC JTC 1/SC 29/WG 11 Moving Picture
Experts Group MPEG2013/N14174, San Jose, USA, January
2014, <https://mpeg.chiariglione.org/standards/mpeg-h/
high-efficiency-video-coding/requirements-extension-hevc-
coding-screen-content>.
[12] Parhy, M., "Game streaming requirement for Future Video
Coding", ISO/IEC JTC 1/SC 29/WG 11 Moving Picture Experts
Group N36771, Warsaw, Poland, June 2015.
[13] Bjontegaard, G., "Calculation of average PSNR differences
between RD-curves", SG 16 VCEG-M33, April 2001,
<https://www.itu.int/wftp3/av-arch/video-site/0104_Aus/>.
[14] Daede, T., Norkin, A., and I. Brailovskiy, "Video Codec
Testing and Quality Measurement", Work in Progress,
Internet-Draft, draft-ietf-netvc-testing-09, 31 January
2020,
<https://tools.ietf.org/html/draft-ietf-netvc-testing-09>.
[15] Wang, Z., Simoncelli, E.P., and A.C. Bovik, "Multiscale
structural similarity for image quality assessment", IEEE
Thirty-Seventh Asilomar Conference on Signals, Systems and
Computers, DOI 10.1109/ACSSC.2003.1292216, November 2003,
<https://ieeexplore.ieee.org/document/1292216>.
[16] Bossen, F., "Common HM test conditions and software
reference configurations", Joint Collaborative Team on
Video Coding (JCT-VC) of the ITU-T Video Coding Experts
Group (ITU-T Q.6/SG 16) and ISO/IEC Moving Picture Experts
Group (ISO/IEC JTC 1/SC 29/WG 11) , Document JCTVC-L1100,
April 2013, <http://phenix.it-
sudparis.eu/jct/doc_end_user/
current_document.php?id=7281>.
[17] ITU-R, "Studio encoding parameters of digital television
for standard 4:3 and wide screen 16:9 aspect ratios",
ITU-R Recommendation BT.601, March 2011,
<https://www.itu.int/rec/R-REC-BT.601/>.
[18] ISO/IEC, "Information technology -- Coding of audio-visual
objects -- Part 10: Advanced video coding", ISO/IEC
DIS 14496-10, <https://www.iso.org/standard/75400.html>.
[19] ISO/IEC, "Information technology -- Coding of audio-visual
objects -- Part 15: Carriage of network abstraction layer
(NAL) unit structured video in the ISO base media file
format", ISO/IEC 14496-15,
<https://www.iso.org/standard/74429.html>.
[20] ITU-R, "Parameter values for the HDTV standards for
production and international programme exchange", ITU-R
Recommendation BT.709, June 2015,
<https://www.itu.int/rec/R-REC-BT.709>.
Acknowledgments
The authors would like to thank Mr. Paul Coverdale, Mr. Vasily
Rufitskiy, and Dr. Jianle Chen for many useful discussions on this
document and their help while preparing it, as well as Mr. Mo Zanaty,
Dr. Minhua Zhou, Dr. Ali Begen, Mr. Thomas Daede, Mr. Adam Roach,
Dr. Thomas Davies, Mr. Jonathan Lennox, Dr. Timothy Terriberry,
Mr. Peter Thatcher, Dr. Jean-Marc Valin, Mr. Roman Danyliw, Mr. Jack
Moffitt, Mr. Greg Coppa, and Mr. Andrew Krupiczka for their valuable
comments on different revisions of this document.
Authors' Addresses
Alexey Filippov
Huawei Technologies
Email: alexey.filippov@huawei.com
Andrey Norkin
Netflix
Email: anorkin@netflix.com
Jose Roberto Alvarez
Huawei Technologies
Email: j.alvarez@ieee.org