Fast HEVC to SCC Transcoding Based on Decision Trees

Wei Kuang, Yui Lam Chan, Sik Ho Tsang, Wan Chi Siu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Screen Content Coding (SCC) is an extension of the High-Efficiency Video Coding (HEVC) for encoding screen content videos. However, there are many legacy screen content videos already encoded by HEVC. To efficiently migrate screen content videos from the existing HEVC to the emerging SCC, a machine learning based fast transcoding algorithm is proposed by using decision trees in this paper. To speed up the transcoding process, the intermediate data from both the HEVC decoder side and the SCC encoder side are jointly analyzed. Then the optimal coding unit (CU) sizes are mapped from HEVC to SCC while the mode candidates are adaptively checked according to the decision tree outcomes in the re-encoding process. Experimental results show that an average of 48.20% re-encoding time reduction is achieved with only 1.47% Bjontegaard delta bitrate loss using All Intra (AI) configuration.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Multimedia and Expo, ICME 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781538617373
DOIs
Publication statusPublished - 23 Jul 2018
Event2018 IEEE International Conference on Multimedia and Expo, ICME 2018 - San Diego, United States
Duration: 23 Jul 201827 Jul 2018

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
Volume2018-July
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

Conference2018 IEEE International Conference on Multimedia and Expo, ICME 2018
Country/TerritoryUnited States
CitySan Diego
Period23/07/1827/07/18

Keywords

  • High Efficiency Video Coding
  • machine learning
  • Screen Content Coding
  • Transcoding

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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