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author:

Zhang, J. (Zhang, J..) [1] | Kwong, S.T.W. (Kwong, S.T.W..) [2] | Zhao, T. (Zhao, T..) [3] | Ip, H.H.S. (Ip, H.H.S..) [4]

Indexed by:

Scopus

Abstract:

A large number of industrial video applications are expected to work in real-time and power-constrained scenarios. For such applications, the coding complexity has a great impact on their performance. In this paper, we propose a complexity control method in the high-efficiency video coding intracoding to facilitate these video applications. The proposed method is performed on the coding tree unit (CTU) level, which consists of three steps, namely complexity estimation, complexity allocation, and prediction unit (PU) adaption. In the first step, a complexity estimation model is proposed to estimate the coding complexity of each CTU based on the sum of absolute transformed difference. Then, the complexity budget is allocated to each CTU proportionally to its estimated coding complexity. In PU adaption, only a subset of PU sizes are selected for the CTU according to its allocated complexity and prediction performance. A feedback-based error elimination scheme removes the complexity error during the encoding process. Experimental results show that the proposed method is able to adjust the complexity ratio from 100% to 20%. Meanwhile, the rate-distortion performance and complexity control accuracy of the proposed method are superior to those of the state-of-the-art methods. © 2005-2012 IEEE.

Keyword:

complexity allocation; Complexity control; complexity estimation; high-efficiency video coding (HEVC); prediction unit (PU) adaption

Community:

  • [ 1 ] [Zhang, J.]Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong
  • [ 2 ] [Kwong, S.T.W.]Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong
  • [ 3 ] [Zhao, T.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 4 ] [Ip, H.H.S.]Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong

Reprint 's Address:

  • [Kwong, S.T.W.]Department of Computer Science, City University of Hong KongHong Kong

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Source :

IEEE Transactions on Industrial Informatics

ISSN: 1551-3203

Year: 2019

Issue: 3

Volume: 15

Page: 1437-1440

9 . 1 1 2

JCR@2019

1 1 . 7 0 0

JCR@2023

ESI HC Threshold:150

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 16

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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