The Joint Exploration Model (JEM) for Video Compression With Capability Beyond HEVC

This paper provides an overview of the coding algorithms of the Joint Exploration Model (JEM) for video compression with capability beyond HEVC, which was developed by the Joint Video Exploration Team (JVET) of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems for video technology 2020-05, Vol.30 (5), p.1208-1225
Main Authors: Chen, Jianle, Karczewicz, Marta, Huang, Yu-Wen, Choi, Kiho, Ohm, Jens-Rainer, Sullivan, Gary J.
Format: Article
Language:English
Subjects:
Algorithms
Coding
Coding standards
Encoding
Experimentation
Exploration
High efficiency video coding
high efficiency video coding (HEVC)
Joint exploration model (JEM)
joint video exploration team (JVET)
moving picture experts group (MPEG)
Transform coding
Transforms
versatile video coding (VVC)
video coding experts group (VCEG)
Video compression
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Summary:This paper provides an overview of the coding algorithms of the Joint Exploration Model (JEM) for video compression with capability beyond HEVC, which was developed by the Joint Video Exploration Team (JVET) of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). The goal of the JEM development and experimentation was to provide evidence that sufficient coding efficiency improvement over the High Efficiency Video Coding (HEVC) standard can be achieved, which would justify the need for a new video coding standard with a compression capability significantly exceeding that of HEVC. The development of the JEM provided an ability to conduct studies toward that goal in a verifiable and collaborative manner and led to the launching of the project to develop the new Versatile Video Coding (VVC) standard. Objective metric gains exceeding 30% were measured for most of the tested high-resolution video content that represents current demanding new applications, and subjective testing using human observers showed even more benefit.
ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2019.2945830