Ultra Fast Screen Content Coding via Random Forest

Sik Ho Tsang, Ngai Wing Kwong, Yui Lam Chan

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

Abstract

Screen content coding (SCC) is an extension to High Efficiency Video Coding (HEVC) used to compress screen content videos. Besides the conventional intra (INTRA) mode, new coding tools, intra block copy (IBC), palette (PLT) modes, and adaptive color-space transform (ACT) are introduced to encode screen content (SC) such as texts and graphics. However, the use of IBC, PLT and ACT increases the encoder complexity though coding efficiency can be improved. While there were numerous approaches for fast INTRA, fast IBC and fast PLT at coding unit (CU) level, we propose fast prediction unit (PU) decisions for INTRA and IBC. In addition, fast ACT approach is also proposed. Both approaches reduce the encoder complexity of SCC by making use of SC characteristics, neighbor correlations, and intermediate cost information via random forest (RF). Experimental results show that, with also fast CU mode decision approaches at CU level, our proposed approach, namely HoFastRF, can obtain 51.29% average encoding time reduction with only 1.45% increase in Bjontegaard delta bitrate (BD-rate). It is the first fast SCC approach to obtain over 50% average encoding time reduction with less than 1.5% increase in BD-rate.

Original languageEnglish
Title of host publication2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1112-1117
Number of pages6
ISBN (Electronic)9789881476883
Publication statusPublished - 7 Dec 2020
Event2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Virtual, Auckland, New Zealand
Duration: 7 Dec 202010 Dec 2020

Publication series

Name2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings

Conference

Conference2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020
Country/TerritoryNew Zealand
CityVirtual, Auckland
Period7/12/2010/12/20

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Signal Processing
  • Decision Sciences (miscellaneous)
  • Instrumentation

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