Deep Neural Network Based Video Compression for Next Generation MPEG Video Codec Standardization
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Versatile Video Coding – the Next-Generation Video Standard of the Joint Video Experts Team
31.07.2018 Versatile Video Coding – The Next-Generation Video Standard of the Joint Video Experts Team Mile High Video Workshop, Denver July 31, 2018 Gary J. Sullivan, JVET co-chair Acknowledgement: Presentation prepared with Jens-Rainer Ohm and Mathias Wien, Institute of Communication Engineering, RWTH Aachen University 1. Introduction Versatile Video Coding – The Next-Generation Video Standard of the Joint Video Experts Team 1 31.07.2018 Video coding standardization organisations • ISO/IEC MPEG = “Moving Picture Experts Group” (ISO/IEC JTC 1/SC 29/WG 11 = International Standardization Organization and International Electrotechnical Commission, Joint Technical Committee 1, Subcommittee 29, Working Group 11) • ITU-T VCEG = “Video Coding Experts Group” (ITU-T SG16/Q6 = International Telecommunications Union – Telecommunications Standardization Sector (ITU-T, a United Nations Organization, formerly CCITT), Study Group 16, Working Party 3, Question 6) • JVT = “Joint Video Team” collaborative team of MPEG & VCEG, responsible for developing AVC (discontinued in 2009) • JCT-VC = “Joint Collaborative Team on Video Coding” team of MPEG & VCEG , responsible for developing HEVC (established January 2010) • JVET = “Joint Video Experts Team” responsible for developing VVC (established Oct. 2015) – previously called “Joint Video Exploration Team” 3 Versatile Video Coding – The Next-Generation Video Standard of the Joint Video Experts Team Gary Sullivan | Jens-Rainer Ohm | Mathias Wien | July 31, 2018 History of international video coding standardization -
Overview of Technologies for Immersive Visual Experiences: Capture, Processing, Compression, Standardization and Display
Overview of technologies for immersive visual experiences: capture, processing, compression, standardization and display Marek Domański Poznań University of Technology Chair of Multimedia Telecommunications and Microelectronics Poznań, Poland 1 Immersive visual experiences • Arbitrary direction of viewing System : 3DoF • Arbitrary location of viewer - virtual navigation - free-viewpoint television • Both System : 6DoF Virtual viewer 2 Immersive video content Computer-generated Natural content Multiple camera around a scene also depth cameras, light-field cameras Camera(s) located in a center of a scene 360-degree cameras Mixed e.g.: wearable cameras 3 Video capture Common technical problems • Synchronization of cameras Camera hardware needs to enable synchronization Shutter release error < Exposition interval • Frame rate High frame rate needed – Head Mounted Devices 4 Common task for immersive video capture: Calibration Camera parameter estimation: • Intrinsic – the parameters of individual cameras – remain unchanged by camera motion • Extrinsic – related to camera locations in real word – do change by camera motion (even slight !) Out of scope of standardization • Improved methods developed 5 Depth estimation • By video analysis – from at least 2 video sequences – Computationally heavy – Huge progress recently • By depth cameras – diverse products – Infrared illuminate of the scene – Limited resolution mostly Out of scope of standardization 6 MPEG Test video sequences • Large collection of video sequences with depth information -
Versatile Video Coding (VVC)
Versatile Video Coding (VVC) on the final stretch Benjamin Bross Fraunhofer Heinrich Hertz Institute, Berlin ITU Workshop on “The future of media” © Geneva, Switzerland, 8 October 2019 Versatile Video Coding (VVC) Joint ITU-T (VCEG) and ISO/IEC (MPEG) project Coding Efficiency Versatility 50% over H.265/HEVC Screen content HD / UHD / 8K resolutions Adaptive resolution change 10bit / HDR Independent sub-pictures 2 VVC – Coding Efficiency History of Video Coding Standards H.261 JPEG H.265 / H.264 / H.262 / (1991) (1990) PSNR MPEG-HEVC MPEG-4 AVC MPEG-2 (dB) (2013) (2003) (1995) 40 38 Bit-rate Reduction: 50% 35 36 34 32 30 28 0 100 200 300 bit rate (kbit/s) 3 VVC – Coding Efficiency History of Video Coding Standards H.261 JPEG H.265 / H.264 / H.262 / (1991) (1990) PSNR MPEG-HEVC MPEG-4 AVC MPEG-2 (dB) (2013) (2003) (1995) 40 38 36 Do we need more efficient video coding? 34 32 30 28 0 100 200 300 bit rate (kbit/s) 4 VVC – Coding Efficiency Jevons Paradox "The efficiency with which a resource is used tends to increase (rather than decrease) the rate of consumption of that resource." 5 VVC – Coding Efficiency Target for the final VVC standard H.262 / H.261 JPEG H.??? / H.265 / H.264 / MPEG-2 (1991) (1990) PSNR MPEG-VVC MPEG-HEVC MPEG-4 AVC (dB) (2013) (2003) (1995) 40 38 36 35 Bit-rate Reduction Target: 50% 34 32 30 28 0 100 200 300 bit rate (kbit/s) 6 VVC – Timeline 2015 Oct. – Exploration Phase • Joint Video Exploration Team (JVET) of ITU-T VCEG and ISO/IEC MPEG established October ‘15 in Geneva • Joint Video Exploration Model (JEM) as software playground to explore new coding tools • 34% bitrate savings for JEM relative to HEVC provided evidence to start a new joint standardization activity with a… 2017 Oct. -
Security Solutions Y in MPEG Family of MPEG Family of Standards
1 Security solutions in MPEG family of standards TdjEbhiiTouradj Ebrahimi [email protected] NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG: Moving Picture Experts Group 2 • MPEG-1 (1992): MP3, Video CD, first generation set-top box, … • MPEG-2 (1994): Digital TV, HDTV, DVD, DVB, Professional, … • MPEG-4 (1998, 99, ongoing): Coding of Audiovisual Objects • MPEG-7 (2001, ongo ing ): DitiDescription of Multimedia Content • MPEG-21 (2002, ongoing): Multimedia Framework NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG-1 - ISO/IEC 11172:1992 3 • Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s – Part 1 Systems - Program Stream – Part 2 Video – Part 3 Audio – Part 4 Conformance – Part 5 Reference software NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG-2 - ISO/IEC 13818:1994 4 • Generic coding of moving pictures and associated audio – Part 1 Systems - joint with ITU – Part 2 Video - joint with ITU – Part 3 Audio – Part 4 Conformance – Part 5 Reference software – Part 6 DSM CC – Par t 7 AAC - Advance d Au dio Co ding – Part 9 RTI - Real Time Interface – Part 10 Conformance extension - DSM-CC – Part 11 IPMP on MPEG-2 Systems NET working? Broadcast Networks and their security 16-17 June 2004, Geneva, Switzerland MPEG-4 - ISO/IEC 14496:1998 5 • Coding of audio-visual objects – Part 1 Systems – Part 2 Visual – Part 3 Audio – Part 4 Conformance – Part 5 Reference -
The H.264 Advanced Video Coding (AVC) Standard
Whitepaper: The H.264 Advanced Video Coding (AVC) Standard What It Means to Web Camera Performance Introduction A new generation of webcams is hitting the market that makes video conferencing a more lifelike experience for users, thanks to adoption of the breakthrough H.264 standard. This white paper explains some of the key benefits of H.264 encoding and why cameras with this technology should be on the shopping list of every business. The Need for Compression Today, Internet connection rates average in the range of a few megabits per second. While VGA video requires 147 megabits per second (Mbps) of data, full high definition (HD) 1080p video requires almost one gigabit per second of data, as illustrated in Table 1. Table 1. Display Resolution Format Comparison Format Horizontal Pixels Vertical Lines Pixels Megabits per second (Mbps) QVGA 320 240 76,800 37 VGA 640 480 307,200 147 720p 1280 720 921,600 442 1080p 1920 1080 2,073,600 995 Video Compression Techniques Digital video streams, especially at high definition (HD) resolution, represent huge amounts of data. In order to achieve real-time HD resolution over typical Internet connection bandwidths, video compression is required. The amount of compression required to transmit 1080p video over a three megabits per second link is 332:1! Video compression techniques use mathematical algorithms to reduce the amount of data needed to transmit or store video. Lossless Compression Lossless compression changes how data is stored without resulting in any loss of information. Zip files are losslessly compressed so that when they are unzipped, the original files are recovered. -
Download Recent and Forthcoming Books from This Series
River Publishers Book Catalogue Series in Signal, Image and Speech Processing River Publishers Series in Signal, Image and Speech Processing Digital Video Coding for Next Generation Multimedia H.264, HEVC, VVC, EVC Video Compression Authors: Shreyanka Subbarayappa, Ramaiah University of Applied Sciences, India K. R. Rao, University of Texas at Arlington, Texas, U.S.A Humberto Ochoa Domínguez, Universidad Autónoma de Ciudad Juárez, México ISBN: 9788770224215 e-ISBN: 9788770224208 Available From: January 2022 Price: € 98.50 Description: Innovations in communication systems and technology are growing tremendously. In multimedia communication systems, technology has transformed from analog television to digital television in the video domain. Mobile phones are known as smart phones as they are used, not only to make voice calls, but also used to send emails, video calls, transfer data, GPS, taking pictures and so on. Due to the widespread user applications, compression of data becomes important to save system resources. Video occupies 75% of data transfer traffic and is expected to cover 80% by the end of 2021. Video is also continuously increasing in file size from standard definition (SD) to ultra-high definition (UHD - 4K, 8K and 12K) video. More data or size in video requires higher transmission bandwidth or more disk space to store which can be slow and expensive. This drives the improvements in compression and hence the demand for a new codec. Several algorithms are used to achieve compression of Image or Video files, these algorithms working together are classified in terms of codecs and we use different codecs for different applications. Advances in video compression technology reduce the utilization of system resources, like processing time, memory use, network bandwidth and battery life. -
ITC Confplanner DVD Pages Itcconfplanner
Comparative Analysis of H.264 and Motion- JPEG2000 Compression for Video Telemetry Item Type text; Proceedings Authors Hallamasek, Kurt; Hallamasek, Karen; Schwagler, Brad; Oxley, Les Publisher International Foundation for Telemetering Journal International Telemetering Conference Proceedings Rights Copyright © held by the author; distribution rights International Foundation for Telemetering Download date 25/09/2021 09:57:28 Link to Item http://hdl.handle.net/10150/581732 COMPARATIVE ANALYSIS OF H.264 AND MOTION-JPEG2000 COMPRESSION FOR VIDEO TELEMETRY Kurt Hallamasek, Karen Hallamasek, Brad Schwagler, Les Oxley [email protected] Ampex Data Systems Corporation Redwood City, CA USA ABSTRACT The H.264/AVC standard, popular in commercial video recording and distribution, has also been widely adopted for high-definition video compression in Intelligence, Surveillance and Reconnaissance and for Flight Test applications. H.264/AVC is the most modern and bandwidth-efficient compression algorithm specified for video recording in the Digital Recording IRIG Standard 106-11, Chapter 10. This bandwidth efficiency is largely derived from the inter-frame compression component of the standard. Motion JPEG-2000 compression is often considered for cockpit display recording, due to the concern that details in the symbols and graphics suffer excessively from artifacts of inter-frame compression and that critical information might be lost. In this paper, we report on a quantitative comparison of H.264/AVC and Motion JPEG-2000 encoding for HD video telemetry. Actual encoder implementations in video recorder products are used for the comparison. INTRODUCTION The phenomenal advances in video compression over the last two decades have made it possible to compress the bit rate of a video stream of imagery acquired at 24-bits per pixel (8-bits for each of the red, green and blue components) with a rate of a fraction of a bit per pixel. -
Kompresja Statycznego Obrazu 138
Damian Karwowski Zrozumieć Kompresję Obrazu Podstawy Technik Kodowania Stratnego oraz Bezstratnego Obrazów Wydanie Pierwsze, wersja 1.2 Poznań 2019r. ISBN 978-83-953420-0-4 9 788395 342004 © Damian Karwowski – „Zrozumieć Kompresję Obrazu” © Copyright by DAMIAN KARWOWSKI. All rights reserved. Książka jest chroniona prawem autorskim i prawami pokrewnymi. Egzemplarz książki został zdeponowany w Kancelarii Notarialnej. Książka jest dostępna pod adresem: www.zrozumieckompresje.pl ISBN 978-83-953420-0-4 Projekt okładki książki oraz strona internetowa zostały wykonane przez Marka Piskulskiego. Serdecznie dziękuję za profesjonalną pracę Obraz „Miś Panda”, który jest częścią okładki, namalowała na płótnie Natalka Karwowska. Natalko, dziękuję Ci za Twój wysiłek Autor książki dołożył ogromnych starań, żeby zamieszczone w niej informacje były prawdziwe i rzetelnie przedstawione. Korzystając z książki Czytelnik robi to jednak wyłącznie na własną odpowiedzialność. Tym samym autor nie odpowiada za jakiekolwiek szkody, będące następstwem wykorzystania zawartej w książce wiedzy. Autor książki Dr inż. Damian Karwowski. Absolwent Politechniki Poznańskiej. Uzyskał tytuł zawodowy magistra inżyniera oraz stopień doktora nauk technicznych na Politechnice Poznańskiej, odpowiednio w latach 2003 i 2008. Obecnie pracownik naukowo-dydaktyczny na wyżej wymienionej uczelni. Od roku 2003 zawodowo zajmuje się kompresją obrazu. Autor ponad 50 publikacji naukowych o tematyce kompresji i przetwarzania obrazów. Brał udział w licznych projektach naukowych dotyczących wydajnej reprezentacji multimedialnych danych. Dodatkowo członek wielu zespołów badawczych, które w tematyce kompresji obrazu i dźwięku realizowały prace badawczo-wdrożeniowe dla przemysłu. Jego zainteresowania obejmują kompresję danych, techniki kodowania entropijnego danych oraz realizację kodeków obrazu i dźwięku na procesorach x86 oraz DSP. 4 | S t r o n a © Damian Karwowski – „Zrozumieć Kompresję Obrazu” Spis treści Spis treści 5 “Słowo” wstępu 11 Rozdział 1 15 Obraz i jego reprezentacja przestrzenna 15 1.1. -
Contribuições À Codificação Eficiente De Imagem E Vídeo Utilizando Recorrência De Padrões Multiescala
CONTRIBUIÇÕES À CODIFICAÇÃO EFICIENTE DE IMAGEM E VÍDEO UTILIZANDO RECORRÊNCIA DE PADRÕES MULTIESCALA Nelson Carreira Francisco Tese de Doutorado apresentada ao Programa de Pós-graduação em Engenharia Elétrica, COPPE, da Universidade Federal do Rio de Janeiro, como parte dos requisitos necessários à obtenção do título de Doutor em Engenharia Elétrica. Orientadores: Eduardo Antônio Barros da Silva Nuno Miguel Morais Rodrigues Rio de Janeiro Novembro de 2012 CONTRIBUIÇÕES À CODIFICAÇÃO EFICIENTE DE IMAGEM E VÍDEO UTILIZANDO RECORRÊNCIA DE PADRÕES MULTIESCALA Nelson Carreira Francisco TESE SUBMETIDA AO CORPO DOCENTE DO INSTITUTO ALBERTO LUIZ COIMBRA DE PÓS-GRADUAÇÃO E PESQUISA DE ENGENHARIA (COPPE) DA UNIVERSIDADE FEDERAL DO RIO DE JANEIRO COMO PARTE DOS REQUISITOS NECESSÁRIOS PARA A OBTENÇÃO DO GRAU DE DOUTOR EM CIÊNCIAS EM ENGENHARIA ELÉTRICA. Examinada por: Prof. Eduardo Antônio Barros da Silva, Ph.D. Prof. Nuno Miguel Morais Rodrigues, Ph.D Prof. Sérgio Lima Netto, Ph.D. Prof. José Gabriel Rodriguez Carneiro Gomes, Ph.D. Prof. Ricardo Lopes de Queiroz, Ph.D Prof. Carla Liberal Pagliari, Ph.D RIO DE JANEIRO, RJ – BRASIL NOVEMBRO DE 2012 Francisco, Nelson Carreira Contribuições à Codificação Eficiente de Imagem e Vídeo Utilizando Recorrência de Padrões Multiescala/Nelson Carreira Francisco. – Rio de Janeiro: UFRJ/COPPE, 2012. XXII, 270 p.: il.; 29, 7cm. Orientadores: Eduardo Antônio Barros da Silva Nuno Miguel Morais Rodrigues Tese (doutorado) – UFRJ/COPPE/Programa de Engenharia Elétrica, 2012. Referências Bibliográficas: p. 257 – 270. 1. Casamento de Padrões Multiescalas. 2. Compressão de imagens estáticas. 3. Compressão de Documentos Compostos. 4. Compressão de Vídeo. 5. Filtragem de Redução de Efeito de Bloco. I. da Silva, Eduardo Antônio Barros et al. -
The H.264/MPEG4 Advanced Video Coding Standard and Its Applications
SULLIVAN LAYOUT 7/19/06 10:38 AM Page 134 STANDARDS REPORT The H.264/MPEG4 Advanced Video Coding Standard and its Applications Detlev Marpe and Thomas Wiegand, Heinrich Hertz Institute (HHI), Gary J. Sullivan, Microsoft Corporation ABSTRACT Regarding these challenges, H.264/MPEG4 Advanced Video Coding (AVC) [4], as the latest H.264/MPEG4-AVC is the latest video cod- entry of international video coding standards, ing standard of the ITU-T Video Coding Experts has demonstrated significantly improved coding Group (VCEG) and the ISO/IEC Moving Pic- efficiency, substantially enhanced error robust- ture Experts Group (MPEG). H.264/MPEG4- ness, and increased flexibility and scope of appli- AVC has recently become the most widely cability relative to its predecessors [5]. A recently accepted video coding standard since the deploy- added amendment to H.264/MPEG4-AVC, the ment of MPEG2 at the dawn of digital televi- so-called fidelity range extensions (FRExt) [6], sion, and it may soon overtake MPEG2 in further broaden the application domain of the common use. It covers all common video appli- new standard toward areas like professional con- cations ranging from mobile services and video- tribution, distribution, or studio/post production. conferencing to IPTV, HDTV, and HD video Another set of extensions for scalable video cod- storage. This article discusses the technology ing (SVC) is currently being designed [7, 8], aim- behind the new H.264/MPEG4-AVC standard, ing at a functionality that allows the focusing on the main distinct features of its core reconstruction of video signals with lower spatio- coding technology and its first set of extensions, temporal resolution or lower quality from parts known as the fidelity range extensions (FRExt). -
H.264/MPEG-4 Advanced Video Coding Alexander Hermans
Seminar Report H.264/MPEG-4 Advanced Video Coding Alexander Hermans Matriculation Number: 284141 RWTH September 11, 2012 Contents 1 Introduction 2 1.1 MPEG-4 AVC/H.264 Overview . .3 1.2 Structure of this paper . .3 2 Codec overview 3 2.1 Coding structure . .3 2.2 Encoder . .4 2.3 Decoder . .6 3 Main differences 7 3.1 Intra frame prediction . .7 3.2 Inter frame prediction . .9 3.3 Transform function . 11 3.4 Quantization . 12 3.5 Entropy encoding . 14 3.6 In-loop deblocking filter . 15 4 Profiles and levels 16 4.1 Profiles . 17 4.2 Levels . 18 5 Evaluation 18 6 Patents 20 7 Summary 20 1 1 Introduction Since digital images have been created, the need for compression has been clear. The amount of data needed to store an uncompressed image is large. But while it still might be feasible to store a full resolution uncompressed image, storing video sequences without compression is not. Assuming a normal frame-rate of about 25 frames per second, the amount of data needed to store one hour of high definition video is about 560GB1. Compressing each image on its own, would reduce this amount, but it would not make the video small enough to be stored on today's typical storage mediums. To overcome this problem, video compression algorithms have exploited the temporal redundancies in the video frames. By using previously encoded, or decoded, frames to predict values for the next frame, the data can be compressed with such a rate that storage becomes feasible. -
Introduction to the Special Issue on Scalable Video Coding—Standardization and Beyond
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 17, NO. 9, SEPTEMBER 2007 1099 Introduction to the Special Issue on Scalable Video Coding—Standardization and Beyond FEW YEARS ago, the subject of video coding received of scalability, this one is perhaps the most difficult to design Aa large amount of skepticism. The basic argument was in a way that is both effective (from a compression capability that the 1990s generation of international standards was close point of view) and practical for implementation in terms of to the asymptotic limit of compression capability—or at least computational resource requirements. Finally, there is quality was good enough that there would be little market interest in scalability, sometimes also referred to as SNR or fidelity scala- something else. Moreover, there was the fear that a new video bility, in which the enhancement layer provides an increase in codec design created by an open committee process would in- video quality without changing the picture resolution. evitably contain so many compromises and take so long to be For example, 1080p50/60 enhancement of today’s 720p50/60 completed that it would fail to meet real industry needs or to be or 1080i25/30 HDTV can be deployed as a premium service state-of-the-art in capability when finished. while retaining full compatibility with deployed receivers, or The Joint Video Team (JVT) then proved those views HDTV can be deployed as an enhancement of SDTV video to be wrong and revitalized the field of video coding with services. Another example is low-delay adaptation for multi- the 2003 creation of the H.264/AVC standard (ITU-T Rec.