H.264 video coding with multiple weighted prediction models

Sik Ho Tsang, Yui Lam Chan

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

6 Citations (Scopus)


Weighted prediction is a video coding tool to encode scenes with brightness variations. However, no single WP model works well for all types of brightness variations. In this paper, a novel single reference frame multiple WP models (SRefMWP) scheme is proposed to facilitate the use of multiple WP models in different macroblocks of the current frame even when they are predicted from the same reference. It provides this feature by making a new arrangement of the multiple frame buffers in multiple reference frame motion estimation. Experimental results show that the proposed SRefMWP can improve prediction in scenes with different types of brightness variations, and even benefit to scenes that contain local brightness variation.
Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Number of pages4
Publication statusPublished - 1 Dec 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sep 201029 Sep 2010


Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong
CityHong Kong


  • Brightness variations
  • H.264
  • Multiple reference frames
  • Weighted prediction

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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