Fast CU Partition Decision Algorithm for AVS3 Intra Coding

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Tong Wu
  • Shiyi Liu
  • Feng Wang
  • Zhenyu Wang
  • Rongjie Wang
  • And 1 others
  • Ronggang Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number9314148
Pages (from-to)7540-7549
Journal / PublicationIEEE Access
Volume9
Online published5 Jan 2021
Publication statusPublished - 2021

Link(s)

Abstract

The third generation of Audio Video coding Standard (AVS3) is an emerging video coding standard that surpasses High Efficiency Video Coding (HEVC). AVS3 allows flexible block subdivision by applying Quad-Tree (QT), Binary-Tree (BT) plus Extend Quad-Tree (EQT) partition structure, while the increased flexibility comes at the cost of enormous coding complexity. In this paper, an ingenious early termination mechanism is proposed to skip unnecessary exhaustive searches of the whole tree branches. We carry out a series of restrictive measures based on Coding Unit (CU) size and iteration status to make the sophisticated EQT split mode concentrate more on small CUs with complex texture structure. Historical QTBT partition information is also adopted as an important factor to skip EQT split mode in advance. Meanwhile, a fast CU partition algorithm based on the gradient is proposed to skip horizontal or vertical BT/EQT partition of CUs with prominent texture structure in another direction, in which early termination can be directly conducted in homogenous areas at the same time. Extensive experiments demonstrate that the proposed method can save 43% encoding time with only 0.53% BDBR increase on average under All Intra(AI) configuration, which outperforms the preexisting fast algorithms.

Research Area(s)

  • AVS3, extend quad-tree, fast CU partition decision, gradient, intra coding, texture complexity analysis

Citation Format(s)

Fast CU Partition Decision Algorithm for AVS3 Intra Coding. / Wu, Tong; Liu, Shiyi; Wang, Feng; Wang, Zhenyu; Wang, Rongjie; Wang, Ronggang.

In: IEEE Access, Vol. 9, 9314148, 2021, p. 7540-7549.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review