A Survey on Recent Advances in Video Coding Technologies and Future Research Directions

被引：0

作者：

Guo, Houbang ^{[1
]}

Zhou, Yun ^{[2
]}

Guo, Hongwei ^{[3
]}

Jiang, Zhuqing ^{[4
]}

He, Tian ^{[4
]}

Wu, Yiyan ^{[5
]}

机构：

[1] UCL, Phys & Astron Dept, London WC1E 6BT, England

[2] NRTA, Acad Broadcasting Sci, TV Technol Inst, Beijing 100866, Peoples R China

[3] Honghe Univ, Sch Engn, Mengzi 661100, Peoples R China

[4] Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China

[5] Western Univ, Dept Elect & Comp Engn, London, ON N6A 5B9, Canada

来源：

IEEE TRANSACTIONS ON BROADCASTING | 2025年

基金：

中国国家自然科学基金;

关键词：

Video coding; Encoding; Machine vision; Standards; Color; Streaming media; Transforms; Video recording; Video compression; Quantization (signal); Video coding standards; versatile video coding (VVC); beyond VVC; machine vision; HEVC;

D O I：

10.1109/TBC.2025.3553306

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

With the evolution of video coding, balancing video compression efficiency with quality has become a critical challenge for researchers and the industry. The development of the next-generation video coding standards, such as Versatile Video Coding (VVC), signifies a significant leap in supporting high-resolution formats including 8K, HDR, and WCG. Currently, machine vision has emerged as a rising research focus, driven by breakthrough in Artificial Intelligence and its growing role in content generation, production, distribution, and storage in multimedia applications. This paper presents a comprehensive survey of the video coding tools in the VVC standard. Additionally, we examine recent research in next-generation video coding, particularly in Beyond VVC and end-to-end coding frameworks. Developments in shared human-machine vision systems are also discussed, emphasizing their relevance in evolving multimedia applications. Finally, this paper provides an outlook on video coding standards, considering their potential to drive next-generation multimedia technologies.

引用

页数：6

共 45 条

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