Smoothed reference inter-layer texture prediction for bit depth scalable video coding

Zhan Ma, Jiancong Luo, Peng Yin, Cristina Gomila, Yao Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We present a smoothed reference inter-layer texture prediction mode for bit depth scalability based on the Scalable Video Coding extension of the H.264/MPEG-4 AVC standard. In our approach, the base layer encodes an 8-bit signal that can be decoded by any existing H.264/MPEG-4 AVC decoder and the enhancement layer encodes a higher bit depth signal (e.g. 10/12-bit) which requires a bit depth scalable decoder. The approach presented uses base layer motion vectors to conduct motion compensation upon enhancement layer reference frames. Then, the motion compensated block is tone mapped and summed with the co-located base layer residue block prior to being inverse tone mapped to obtain a smoothed reference predictor. In addition to the original inter-/intra-layer prediction modes, the smoothed reference prediction mode enables inter-layer texture prediction for blocks with inter-coded co-located block. The proposed method is designed to improve the coding efficiency for sequences with non-linear tone mapping, in which case we have gains up to 0.4dB over the CGS-based BDS framework.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Visual Information Processing and Communication
StatePublished - 2010
EventVisual Information Processing and Communication - San Jose, CA, United States
Duration: Jan 19 2010Jan 21 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherVisual Information Processing and Communication
Country/TerritoryUnited States
CitySan Jose, CA


  • Bit depth scalability
  • Scalable video coding
  • Smoothed reference prediction
  • Texture prediction
  • Tone mapping

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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