• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
搜索

Author:

Duan, Kun (Duan, Kun.) | Liu, Pengyu (Liu, Pengyu.) | Jia, Kebin (Jia, Kebin.) (Scholars:贾克斌) | Feng, Zeqi (Feng, Zeqi.)

Indexed by:

EI Scopus SCIE

Abstract:

A next-generation video coding standard High Efficiency Video Coding (HEVC) provides higher video quality and lower compression bit rate but leads to very high encoding complexity, especially in the quad-tree-based coding tree unit partitioning process. To reduce the computational complexity of HEVC, in this paper, we propose an adaptive quad-tree depth range prediction mechanism. First, the proposed mechanism defines the similar region flag to distinguish between the similar region and the non-similar region. Then, two algorithms, the similar region depth range prediction algorithm and the non-similar region depth range prediction algorithm, are proposed. The similar region depth range prediction algorithm estimates the features of the similar region based on the coding unit depth of this region. The optimal depth of this region can be predicted. The non-similar region depth range prediction algorithm can skip low probability tree nodes based on the depth correlation coefficient, which is calculated based on scene content change. Both the similar region depth range prediction algorithm and the non-similar region depth range prediction algorithm show more than 90% predictive accuracy. Experimental results show that under random access configuration and low delay configuration, the proposed mechanism can yield 28.17% and 32.99% computational complexity reduction with negligible rate distortion performance loss, respectively, compared with HM16.9. The results show that the proposed mechanism is expected to be applied in real-time environments.

Keyword:

CU depth HEVC fast coding spatio-temporal correlation

Author Community:

  • [ 1 ] [Liu, Pengyu]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 2 ] [Liu, Pengyu]Beijing Lab Adv Informat Networks, Beijing 100124, Peoples R China
  • [ 3 ] [Liu, Pengyu]Beijing Univ Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China

Reprint Author's Address:

  • 刘鹏宇

    [Liu, Pengyu]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China

Show more details

Related Keywords:

Related Article:

Source :

IEEE ACCESS

ISSN: 2169-3536

Year: 2018

Volume: 6

Page: 54195-54206

3 . 9 0 0

JCR@2022

JCR Journal Grade:1

Cited Count:

WoS CC Cited Count: 5

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

Online/Total:1230/10606614
Address:BJUT Library(100 Pingleyuan,Chaoyang District,Beijing 100124, China Post Code:100124) Contact Us:010-67392185
Copyright:BJUT Library Technical Support:Beijing Aegean Software Co., Ltd.