Computational complexity reduction for HEVC intra prediction with SVM

Han Yuan Hsu, Shang En Huang, Yinyi Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Unlike most researches focus on computation reduction, the fast algorithm proposed in this paper aims at maintaining the coding efficiency as high as possible. In the proposed algorithm we employ support vector machine (SVM) that uses three parameters as features: variances, low-frequency AC components of DCT and spatially neighboring CU levels for fast CU size decision. In addition, based upon RMD cost we propose an adaptive mode candidates method for further RDO computation. Experimental results demonstrate that average 22% reduction of computational complexity can be achieved but only with 0.09% BD bit rate increase.

Original languageEnglish
Title of host publication2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-2
Number of pages2
ISBN (Electronic)9781509040452
DOIs
StatePublished - 19 Dec 2017
Event6th IEEE Global Conference on Consumer Electronics, GCCE 2017 - Nagoya, Japan
Duration: 24 Oct 201727 Oct 2017

Publication series

Name2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
Volume2017-January

Conference

Conference6th IEEE Global Conference on Consumer Electronics, GCCE 2017
Country/TerritoryJapan
CityNagoya
Period24/10/1727/10/17

Keywords

  • computational complexity
  • high efficiency video coding (HEVC)
  • intra prediction

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