Low-complexity Wyner-Ziv video coding based on robust media hashing

Li Wei Kang, Chun Shien Lu*

*Corresponding author for this work

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

6 Citations (Scopus)

Abstract

To meet the requirement of distributed video coding in resource-limited sensor networks, Wyner-Ziv theorem-based source coding with side information available at the decoder states that an intraframe encoder with interframe decoder system can achieve comparable coding efficiency of a conventional video codec. Most existing Wyner-Ziv video coding systems are with light encoder and heavy decoder. In this paper, a new content-aware media hash-based Wyner-Ziv video codec with light encoder and light decoder is proposed. The key is that the significant differences between a video frame and its reference frame are efficiently extracted and used for frame recovery based on robust image hashing without needing to perform motion estimation. The particular contribution of our method is its low complexity in both the encoder and decoder sides. Simulation results demonstrate the achievable coding efficiency of our method in particular for videos with small and middle motions.

Original languageEnglish
Title of host publication2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006
PublisherIEEE Computer Society
Pages267-272
Number of pages6
ISBN (Print)0780397517, 9780780397514
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006 - Victoria, BC, Canada
Duration: 2006 Oct 32006 Oct 6

Publication series

Name2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006

Conference

Conference2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006
Country/TerritoryCanada
CityVictoria, BC
Period2006/10/032006/10/06

Keywords

  • Distributed video coding
  • Media hash
  • Video sensor network
  • Wireless video communication
  • Wyner-Ziv video coding

ASJC Scopus subject areas

  • Signal Processing

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