Network Working Group                                       A. Filippov
Internet Draft                                      Huawei Technologies
Intended status: Informational                                A. Norkin
                                                                Netflix
                                                           J.R. Alvarez
                                                    Huawei Technologies
Expires: March 20, 2017                              September 20, 2016



           <Video Codec Requirements and Evaluation Methodology>
                   draft-ietf-netvc-requirements-03.txt


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   respect 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.

Abstract

   This document provides requirements for a video codec designed
   mainly for use over the Internet. In addition, this document
   describes an evaluation methodology needed for measuring the
   compression efficiency to ensure whether the stated requirements are
   fulfilled or not.

   Table of Contents

   1. Introduction...................................................3
   2. Applications...................................................3
      2.1. Internet Video Streaming..................................4
      2.2. Internet Protocol Television (IPTV).......................4
      2.3. Video conferencing........................................7
      2.4. Video sharing.............................................8
      2.5. Screencasting.............................................9
      2.6. Game streaming...........................................10
      2.7. Video monitoring / surveillance..........................11
   3. Requirements..................................................12
      3.1. General requirements.....................................14
      3.2. Basic requirements.......................................14
         3.2.1. Input source formats:...............................14
         3.2.2. Coding delay........................................14
         3.2.3. Complexity..........................................14
         3.2.4. Scalability.........................................15
         3.2.5. Error resilience....................................15
      3.3. Optional requirements....................................15
         3.3.1. Input source formats................................15
         3.3.2. Scalability.........................................15
         3.3.3. Complexity..........................................16
   4. Evaluation methodology........................................16
      4.1. Compression performance evaluation.......................16
      4.2. Reference software.......................................16
   5. Security Considerations.......................................19
   6. Conclusions...................................................19
   7. References....................................................20
      7.1. Normative References.....................................20
      7.2. Informative References...................................20
   8. Acknowledgments...............................................21
   Appendix A. Abbreviations used in the text of this document......22
   Appendix B. Used terms...........................................23


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1. Introduction

   In this document, the requirements for a video codec designed mainly
   for use over the Internet are presented. 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 / 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
   packet-loss networks. 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 possible amount of delay and the
   necessity of error robust video streams:

   o  If an amount of delay is not crucial for an application, then
      reliable transport protocols such as TCP that resends undelivered
      packets can be used to guarantee correct decoding of transmitted
      data.

   o  If the amount of delay must be kept low, then either data
      transmission should be error free (e.g., by using managed
      networks) or compressed video stream should be error resilient.

   Thus, error resilience can be useful for delay-critical applications
   to provide low delay in packet-loss environment.

2. Applications

   In this chapter, 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, and hence there are different types of
   communication channels involved (e.g., wired or wireless channels)
   that are characterized by different quality of service as well as
   bandwidth; for instance, wired channels are considerably more error-
   free than wireless channels and therefore require different QoS
   approaches. The target platform, the channel bandwidth and the
   channel quality determine resolutions, frame-rates and quality or
   bit-rates for video streams to be encoded or decoded. By default,



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   color format YCbCr 4:2:0 is assumed for the application scenarios
   listed below.

2.1. 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 below.

   +----------------------+-------------------------+-----------------+
   |      Resolution  *   |     Frame-rate, fps     |       PAM       |
   +----------------------+-------------------------+-----------------+
   +----------------------+-------------------------+-----------------+
   |    4K, 3840x2160     |    24/1.001, 24, 25,    |       RA        |
   +----------------------+                         +-----------------+
   | 2K (1080p), 1920x1080|    30/1.001, 30, 50,    |       RA        |
   +----------------------+                         +-----------------+
   |   1080i, 1920x1080*  |    60/1.001, 60, 100,   |       RA        |
   +----------------------+                         +-----------------+
   |    720p, 1280x720    |      120/1.001, 120     |       RA        |
   +----------------------+                         +-----------------+
   | 576p (EDTV), 720x576 | The set of frame-rates  |       RA        |
   +----------------------+                         +-----------------+
   | 576i (SDTV), 720x576*| presented in this table |       RA        |
   +----------------------+                         +-----------------+
   | 480p (EDTV), 720x480 |  is taken from Table 2  |       RA        |
   +----------------------+                         +-----------------+
   | 480i (SDTV), 720x480*|          in [1]         |       RA        |
   +----------------------+                         +-----------------+
   |       512x384        |                         |       RA        |
   +----------------------+                         +-----------------+
   |    QVGA, 320x240     |                         |       RA        |
   +----------------------+-------------------------+-----------------+
   Table 1. Internet Video Streaming: typical values of resolutions,
   frame-rates, and RAPs

   NB *: 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 progressive format.




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   A video encoding pipeline in on-demand Internet video streaming
   typically operates as follows:

   o  Video is encoded in the cloud by software encoders.

   o  Source video is split into chunks, each of which is encoded
      separately, in parallel.

   o  Closed-GOP encoding with 2-5 second intra-picture intervals (or
      more) is used.

   o  Encoding is perceptually optimized. Perceptual quality is
      important and should be considered during the codec development.

   Characteristics and requirements of this application scenario are as
   follows:

   o  High encoder complexity (up to 10x and more) can be tolerated
      since encoding happens once and in parallel for different
      segments.

   o  Decoding complexity should be kept at reasonable levels to enable
      efficient decoder implementation.

   o  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), high frame-rate content are
          important use cases, the codec should be able to encode such
          content efficiently.

       . Coding efficiency improvement 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 the streaming movie-type content and is usually a
          part of the creative intent.





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   o  Significant improvements in compression efficiency between
      generations of video standards are desirable since this scenario
      typically assumes long-term support of legacy video codecs.

   o  Random access points are inserted frequently (one per 2-5
      seconds) to enable switching between resolutions and fast-forward
      playback.

   o  Elementary stream should have a model that allows easy parsing
      and identification of the sample components.

   o  Middle QP values are normally used in streaming, this is also the
      range where compression efficiency is important for this
      scenario.

   o  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.

2.2. 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:

   o  unicast (e.g., for video on demand), where delay is not crucial;

   o  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 Random access to pictures, i.e. random access
   period (RAP) should be kept small enough (approximately, 1-5
   seconds). Optional requirements are as follows:

   o  Temporal (frame-rate) scalability;

   o  Resolution and quality (SNR) scalability.

   For this application, typical values of resolutions, frame-rates,
   and RAPs are presented in Table 2.






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   +----------------------+-------------------------+-----------------+
   |      Resolution  *   |     Frame-rate, fps     |       PAM       |
   +----------------------+-------------------------+-----------------+
   +----------------------+-------------------------+-----------------+
   | 2160p (4K),3840x2160 |    24/1.001, 24, 25,    |       RA        |
   +----------------------+                         +-----------------+
   |   1080p, 1920x1080   |    30/1.001, 30, 50,    |       RA        |
   +----------------------+                         +-----------------+
   |   1080i, 1920x1080*  |    60/1.001, 60, 100,   |       RA        |
   +----------------------+                         +-----------------+
   |    720p, 1280x720    |      120/1.001, 120     |       RA        |
   +----------------------+                         +-----------------+
   | 576p (EDTV), 720x576 | The set of frame-rates  |       RA        |
   +----------------------+                         +-----------------+
   | 576i (SDTV), 720x576*| presented in this table |       RA        |
   +----------------------+                         +-----------------+
   | 480p (EDTV), 720x480 |  is taken from Table 2  |       RA        |
   +----------------------+                         +-----------------+
   | 480i (SDTV), 720x480*|          in [1]         |       RA        |
   +----------------------+-------------------------+-----------------+
   Table 2. IPTV: typical values of resolutions, frame-rates, and RAPs

   NB *: 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 progressive format.

2.3. 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:

   o  Delay should be kept as low as possible (the preferable and
      maximum end-to-end delay values should be less than 100 ms [7]
      and 320 ms [2], respectively);

   o  Temporal (frame-rate) scalability;

   o  Error robustness.

   Support of resolution and quality (SNR) scalability is highly
   desirable. For this application, typical values of resolutions,
   frame-rates, and RAPs are presented in Table 3.



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   +----------------------+-------------------------+----------------+
   |      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 RAPs

2.4. Video sharing

   This is a service that allows people to upload and share video data
   (using live streaming or not) and to watch them. 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
   GoPro or cameras integrated into smartphones (amateur video). The
   main requirements are as follows:

   o  Random access to pictures for downloaded video data;

   o  Temporal (frame-rate) scalability;

   o  Error robustness.

   Support of resolution and quality (SNR) scalability is highly
   desirable. For this application, typical values of resolutions,
   frame-rates, and RAPs are presented in Table 4.

   +----------------------+-------------------------+----------------+
   |      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       |
   +----------------------+-------------------------+----------------+


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   | 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
   [8], and RAPs

2.5. Screencasting

   This is a service that allows users to record and distribute
   computer desktop screen output. This service requires efficient
   compression of computer-generated content with high visual quality
   up to visually and mathematically (numerically) lossless [9].
   Currently, this application includes business presentations
   (powerpoint, word documents, email messages, etc.), animation
   (cartoons), gaming content, data visualization, i.e. such type of
   content that is characterized by fast motion, rotation, smooth
   shade, 3D effect, highly saturated colors with full resolution,
   clear textures and sharp edges with distinct colors [9]), 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, a wide range of video formats (e.g., RGB) in
   addition to YCbCr 4:2:0 and YCbCr 4:4:4 [9]. For this application,
   typical values of resolutions, frame-rates, and RAPs 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  |


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   +----------------------+-------------------------+----------------+
   | 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 RAPs

2.6. Game streaming

   This is a service that provides game content over the Internet to
   different local devices such as notebooks, gaming tablets, etc. In
   this category of applications, server renders 3D games in cloud
   server, and streams the game to any device with a wired or wireless
   broadband connection [10]. There are low latency requirements for
   transmitting user interactions and receiving game data in less than
   a turn-around delay of 100 ms. This allows anyone to play (or
   resume) full featured games from anywhere in the Internet [10]. An
   example of this application is Nvidia Grid [10]. Another category
   application is broadcast of video games played by people over the
   Internet in real time or for later viewing [10]. There are many
   companies such as Twitch, YY in China enable game broadcasting [10].
   Games typically contain a lot of sharp edges and large motion [10].
   The main requirements are as follows:

   o  Random access to pictures for game broadcasting;

   o  Temporal (frame-rate) scalability;



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   o  Error robustness.

   Support of resolution and quality (SNR) scalability is highly
   desirable. For this application, typical values of resolutions,
   frame-rates, and RAPs are similar to ones presented in Table 5.

2.7. Video monitoring / 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 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, respectively. 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 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 RAPs for video monitoring /
   surveillance applications are presented in Table 6.

   +----------------------+-------------------------+-----------------+
   |      Resolution      |     Frame-rate, fps     |       PAM       |
   +----------------------+-------------------------+-----------------+
   +----------------------+-------------------------+-----------------+
   | 2160p (4K),3840x2160 |           12            |    RA, FIZD     |
   +----------------------+-------------------------+-----------------+
   | 5Mpixels, 2560x1920  |           12            |    RA, FIZD     |
   +----------------------+-------------------------+-----------------+
   | 1080p, 1920x1080     |           25            |    RA, FIZD     |
   +----------------------+-------------------------+-----------------+
   | 1.3Mpixels, 1280x960 |         25, 30          |    RA, FIZD     |
   +----------------------+-------------------------+-----------------+
   | 720p, 1280x720       |         25, 30          |    RA, FIZD     |
   +----------------------+-------------------------+-----------------+
   | SVGA, 800x600        |         25, 30          |    RA, FIZD     |
   +----------------------+-------------------------+-----------------+
   Table 6. Video monitoring / surveillance: typical values of
   resolutions, frame-rates, and RAPs






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3. Requirements

   Taking the requirements discussed above for specific video
   applications, this chapter proposes requirements for an internet
   video codec.

3.1. General requirements

   3.1.1. The most basic requirement is coding efficiency, i.e.
   compression performance. The codec should provide higher coding
   efficiency over state-of-the-art video codecs such as HEVC/H.265 and
   VP9, at least by 25% in accordance with the methodology described in
   Section 4.1 of this document. For higher resolutions, the coding
   efficiency improvements are expected to be higher than for lower
   resolutions.

   3.1.2. Good quality specification and well-defined profiles and
   levels are required to enable device interoperability and facilitate
   decoder implementations. 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 bit-rate, line
   buffer size, memory usage, etc.

   +------------------------------------------------------------------+
   |    Level    |  Example picture resolution at highest frame rate  |
   +-------------+----------------------------------------------------+
   |             |           128x96(12,288*)@30.0                     |
   |      1      |           176x144(25,344*)@15.0                    |
   +-------------+----------------------------------------------------+
   |      2      |           352x288(101,376*)@30.0                   |
   +-------------+----------------------------------------------------+
   |             |           352x288(101,376*)@60.0                   |
   |      3      |           640x360(230,400*)@30.0                   |
   +-------------+----------------------------------------------------+
   |             |           640x360(230,400*)@60.0                   |
   |      4      |           960x540(518,400*)@30.0                   |
   +-------------+----------------------------------------------------+
   |             |           720x576(414,720*)@75.0                   |
   |      5      |           960x540(518,400*)@60.0                   |
   |             |           1280x720(921,600*)@30.0                  |
   +-------------+----------------------------------------------------+
   |             |           1,280x720(921,600*)@68.0                 |
   |      6      |           2,048x1,080(2,211,840*)@30.0             |
   +-------------+----------------------------------------------------+
   |             |           1,280x720(921,600*)@120.0                |
   |      7      |           2,048x1,080(2,211,840*)@60.0             |


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   +-------------+----------------------------------------------------+
   |             |           1,920x1,080(2,073,600*)@120.0            |
   |      8      |           3,840x2,160(8,294,400*)@30.0             |
   |             |           4,096x2,160(8,847,360*)@30.0             |
   +-------------+----------------------------------------------------+
   |             |           1,920x1,080(2,073,600*)@250.0            |
   |      9      |           4,096x2,160(8,847,360*)@60.0             |
   +-------------+----------------------------------------------------+
   |             |           1,920x1,080(2,073,600*)@300.0            |
   |     10      |           4,096x2,160(8,847,360*)@120.0            |
   +-------------+----------------------------------------------------+
   |             |           3,840x2,160(8,294,400*)@120.0            |
   |     11      |           8,192x4,320(35,389,440*)@30.0            |
   +-------------+----------------------------------------------------+
   |             |           3,840x2,160(8,294,400*)@250.0            |
   |     12      |           8,192x4,320(35,389,440*)@60.0            |
   +-------------+----------------------------------------------------+
   |             |           3,840x2,160(8,294,400*)@300.0            |
   |     13      |           8,192x4,320(35,389,440*)@120.0           |
   +-------------+----------------------------------------------------+
   Table 7. Codec levels

   NB *: The quantities of pixels are presented for such applications
   where a picture can have an arbitrary size (e.g., screencasting)

   3.1.3. High-level syntax should allow extensibility, so that new
   features can be supported easily by using metadata (e.g., such as
   SEI messages, VUI, headers).

   3.1.4. A bitstream should have a model that allows easy parsing and
   identification of the sample components (such as ISO/IEC14496-10,
   Annex B or ISO/IEC 14496-15). In particular, information needed for
   packet handling (e.g., frame type) should not require parsing
   anything below the header level.

   3.1.5. Perceptual quality tools (such as adaptive QP and
   quantization matrices) should be supported by the codec bit-stream.

   3.1.6. The codec specification shall define a buffer model, such as
   hypothetical reference decoder (HRD).

   3.1.7. Specifications providing integration with system and delivery
   layers should be developed.






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3.2. Basic requirements

   3.2.1. Input source formats:

   o  Bit depth: 8- and 10-bits (up to 12-bits for a high profile) per
      color component;

   o  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)).

   o  For profiles with bit depth of 10 bits per sample or higher,
      support of high dynamic range and wide color gamut.

   o  Support of arbitrary resolution according to the level
      constraints for such applications where a picture can have an
      arbitrary size (e.g., in screencasting).

   3.2.2. Coding delay:

   o  Support of configurations with zero structural delay also
      referred to as "low-delay" configurations.

       . Note 1: end-to-end delay should be up to 320 ms [2] but its
          preferable value should be less than 100 ms [7]

   o  Support of configurations with non-zero structural delay (such as
      out-of-order or multi-pass encoding) for applications without
      low-delay requirements if such configurations provide additional
      compression efficiency improvements.

   3.2.3. Complexity:

   o  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 real-time encoder tools subset should provide
      sufficient improvement in compression efficiency and take into
      account complexity of hardware and software encoder
      implementations.

   o  High-complexity software encoder implementations used by offline
      encoding applications can have 10x or more complexity increase



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      compared to state-of-the-art video compression technologies such
      as HEVC/H.265 and VP9.

   3.2.4. Scalability:

   o  Temporal (frame-rate) scalability should be supported.

   3.2.5. Error resilience:

   o  Error resilience tools that are complementary to the error
      protection mechanisms implemented on transport level should be
      supported.

   o  The codec should support mechanisms that facilitate packetization
      of a bitstream for common network protocols.

   o  Packetization mechanisms should enable frame-level error recovery
      by means of retransmission or error concealment.

   o  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.

   o  The bitstream specification should support independently
      decodable sub-frame units similar to slices or independent tiles.
      It should be possible for the encoder to restrict the bit-stream
      to allow parsing of the bit-stream after a packet-loss and to
      communicate it to the decoder.

3.3. Optional requirements

   3.3.1. Input source formats

   o  Bit depth: up to 16-bits per color component;

   o  Color sampling formats: RGB 4:4:4.

   o  Auxiliary channel (e.g., alpha channel) support.

   3.3.2. Scalability:

   o  Resolution and quality (SNR) scalability that provide low
      compression efficiency penalty (up to 5% of BD-rate [12] increase
      per layer with reasonable increase of both computational and
      hardware complexity) can be supported in the main profile of the



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      codec being developed by the NETVC WG. Otherwise, a separate
      profile is needed to support these types of scalability.

   o  Computational complexity scalability(i.e. computational
      complexity is decreasing along with degrading picture quality) is
      desirable.

   3.3.3. Complexity:

   Tools that enable parallel processing (e.g., slices, tiles, wave
   front propagation processing) at both encoder and decoder sides are
   highly desirable for many applications.

   o  High-level multi-core parallelism: encoder and decoder operation,
      especially entropy encoding and decoding, should allow multiple
      frames or sub-frame regions (e.g. 1D slices, 2D tiles, or
      partitions) to be processed concurrently, either independently or
      with deterministic dependencies that can be efficiently pipelined

   o  Low-level instruction set parallelism: favor algorithms that are
      SIMD/GPU friendly over inherently serial algorithms

3.3.4. Coding efficiency

   Compression efficiency on noisy content, content with film grain,
   computer generated content, and low resolution materials is
   desirable.

4. Evaluation methodology

4.1. Compression performance evaluation

   As shown in Fig.1, compression performance testing is performed in 3
   overlapped ranges that encompass 10 different bitrate values:

   o  Low bitrate range (LBR) is the range that contains the 4 lowest
      bitrates of the 10 specified bitrates (1 of the 4 bitrate values
      is shared with the neighboring range);

   o  Medium bitrate range (MBR) is the range that contains the 4
      medium bitrates of the 10 specified bitrates (2 of the 4 bitrate
      values are shared with the neighboring ranges);

   o  High bitrate range (HBR) is the range that contains the 4 highest
      bitrates of the 10 specified bitrates (1 of the 4 bitrate values
      is shared with the neighboring range).



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   Initially, for the codec selected as a reference one (e.g., HEVC or
   VP9), a set of 10 QP (quantization parameter) values should be
   specified (in a separate document on Internet video codec testing)
   and corresponding quality values should be calculated. In Fig.1, QP
   and quality values are denoted as QP0, QP1, QP2, ..., QP8, QP9 and
   Q0, Q1, Q2, ..., Q8, 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 above described procedure.

   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  <+-----
   +----------------+--------------+--------------+--------->
   ^                ^              ^              ^     Bit-rate
   |-------LBR------|              |-----HBR------|
                    ^              ^
                    |------MBR-----|

   Figure 1 Quality/QP alignment for compression performance evaluation


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   Since the QP mapping results may vary for different sequences,
   eventually, this quality alignment procedure needs to be separately
   performed for each quality assessment index and each sequence used
   for codec performance evaluation to fulfill the above described
   requirements.

   To assess the quality of output (decoded) sequences, two indexes,
   PSNR [3] and MS-SSIM [3,11] 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 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 and 10
   RD-points for MS-SSIM should be calculated in the case of YCbCr
   whereas 60 RD-points (30 for PSNR and 30 for MS-SSIM) should be
   calculated in the case of RGB.

   Finally, to obtain an integral estimation, BD-rate savings [12]
   should be computed for each range and each quality index. In
   addition, average values over all the 3 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 10 QP values for the reference codec
   are defined in a separate document. 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 [13] and Table 8.

   +----------------------+-------------------------------------------+
   | Intra-period, second | HEVC/H.265 encoding mode according to [13]|
   +----------------------+-------------------------------------------+
   |          AI          |        Intra Main or Intra Main10         |
   +----------------------+-------------------------------------------+
   |          RA          |           Random access Main or           |
   |                      |           Random access Main10            |
   +----------------------+-------------------------------------------+
   |         JIZD         |             Low delay Main or             |
   |                      |             Low delay Main10              |
   +----------------------+-------------------------------------------+

   Table 8. Intra-periods for different HEVC/H.265 encoding modes
   according to [13]

   According to the coding efficiency requirement described in Section
   3.1.1, 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,


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   o  25% if calculated over the whole bitrate range;

   o  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, i.e. 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.

4.2. Reference software

   Reference software provided to the NETVC WG for candidate codecs
   should comprise a fully operational encoder supporting necessary
   rate controls, subjective quality optimization features and some
   degree of speed optimization and a "real-time" decoder.

5. 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 cover the worst case of computational
   complexity, memory bandwidth, and physical memory size (e.g., for
   decoded pictures used as references). Otherwise, it can be
   considered as a security vulnerability and lead to denial-of-service
   (DoS) in the case of attacks.

6. Conclusions

   In this document, an overview of Internet video codec applications
   and typical use cases as well as a prioritized list of requirements
   for an Internet video codec are presented. An evaluation methodology
   for this codec is also proposed.




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7. References

7.1. Normative References

   [1]   Recommendation ITU-R BT.2020-2: Parameter values for ultra-
         high definition television systems for production and
         international programme exchange, 2015.

   [2]   Recommendation ITU-T G.1091: Quality of Experience
         requirements for telepresence services, 2014.

   [3]   ISO/IEC PDTR 29170-1: Information technology -- Advanced image
         coding and evaluation methodologies -- Part 1: Guidelines for
         codec evaluation.

   [4]   ISO/IEC 23008-2:2015. Information technology -- High
         efficiency coding and media delivery in heterogeneous
         environments -- Part 2: High efficiency video coding

   [5]   Recommendation ITU-T H.265: High efficiency video coding,
         2013.

   [6]   https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/

7.2. Informative References

   [7]   S. Wenger, "The case for scalability support in version 1 of
         Future Video Coding," contribution COM 16-C 988 R1-E to ITU-T
         SG16/Q6, September 2015."Recommended upload encoding settings
         (Advanced)"

   [8]   "Recommended upload encoding settings (Advanced)"
         https://support.google.com/youtube/answer/1722171?hl=en

   [9]   H. Yu, K. McCann, R. Cohen, and P. Amon, "Requirements for
         future extensions of HEVC in coding screen content", ISO/IEC
         JTC1/SC29/WG11 MPEG2013/N14174, San Jose, USA, Jan. 2014

   [10]  Manindra Parhy, "Game streaming requirement for Future Video
         Coding," MPEG Contribution m36771, June 2015, Warsaw, Poland.

   [11]  Z. Wang, E. P. Simoncelli, and A. C. Bovik, "Multi-scale
         structural similarity for image quality assessment," Invited
         Paper, IEEE Asilomar Conference on Signals, Systems and
         Computers, Nov. 2003, Vol. 2, pp. 1398-1402.




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   [12]  G. Bjontegaard, "Calculation of average PSNR differences
         between RD-curves (VCEG-M33)," in VCEG Meeting (ITU-T SG16
         Q.6), Austin, Texas, USA, Apr. 2-4 2001.

   [13]  F. Bossen, "Common test conditions and software reference
         configurations," JCTVC-L1100, Geneva, Switzerland, Jan. 2013.

   [14]  http://www.digitizationguidelines.gov/term.php?term=compressio
         nvisuallylossless)

8. Acknowledgments

9. The authors would like to thank Mr. Jiantong Zhou, Mr. Paul
   Coverdale, Mr. Vasily Rufitskiy, and Dr. Haitao Yang 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, Dr. Thomas Davies, Mr. Jonathan Lennox, Dr. Timothy
   Terriberry, Mr. Peter Thatcher, Dr. Jean-Marc Valin, Mr. Jack
   Moffitt, Mr. Greg Coppa and Mr. Andrew Krupiczka for their valuable
   comments on different revisions of this document.

   This document was prepared using 2-Word-v2.0.template.dot.



























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Appendix A.                 Abbreviations used in the text of this document

   +--------------+---------------------------------------------------+
   | Abbreviation |                      Meaning                      |
   +--------------+---------------------------------------------------+
   |      AI      | All-Intra (each picture is intra-coded)           |
   |   BD-Rate    | Bjontegaard Delta Rate                            |
   |     FIZD     | just the First picture is Intra-coded, Zero       |
   |              | structural Delay                                  |
   |     GOP      | Group of Picture                                  |
   |     HBR      | High Bitrate Range                                |
   |     HDR      | High Dynamic Range                                |
   |     HRD      | Hypothetical Reference Decoder                    |
   |     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              |
   |     UGC      | User-Generated Content                            |
   |     VDI      | Virtual Desktop Infrastructure                    |
   |     VUI      | Video Usability Information                       |
   |     WCG      | Wide Color Gamut                                  |
   +--------------+---------------------------------------------------+


















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Appendix B.                 Used terms

   +------------------+-----------------------------------------------+
   |      Term        |                   Meaning                     |
   +------------------+-----------------------------------------------+
   | High dynamic     | is a set of techniques that allow a greater   |
   | range imaging    | dynamic range of exposures or values (i.e.,   |
   |                  | a wide 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 such  |
   |                  | examples as exterior scenes that include      |
   |                  | light-colored items struck by direct sunlight |
   |                  | and areas of deep shadow [14].                |
   |                  |                                               |
   | Random access    | is the period of time between two closest     |
   | period           | independently decodable frames (pictures).    |
   |                  |                                               |
   | RD-point         | A point in a 2 dimensional rate-distortion    |
   |                  | space where the values of bitrate and quality |
   |                  | metric are used as x- and y-coordinates,      |
   |                  | respectively                                  |
   |                  |                                               |
   | Visually         | is a form or manner of lossy compression      |
   | lossless         | where the data that are lost after the file   |
   | compression      | is compressed and decompressed is not         |
   |                  | detectable to the eye; the compressed data    |
   |                  | appearing identical to the uncompressed       |
   |                  | data [14].                                    |
   |                  |                                               |
   | Wide color gamut | is a certain complete color subset (e.g.,     |
   |                  | considered in ITU-R BT.2020) 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 or BT.709). |
   +------------------+-----------------------------------------------+










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Authors' Addresses

   Alexey Filippov
   Huawei Technologies

   Email: alexey.filippov@huawei.com


   Andrey Norkin
   Netflix

   Email: anorkin@netflix.com


   Jose Roberto Alvarez
   Huawei Technologies

   Email: jose.roberto.alvarez@huawei.com































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