Region-of-interest based H.264 encoding parameter allocation for low power video communication

Minghui Wang*, Tianruo Zhang, Chen Liu, Satoshi Goto

*Corresponding author for this work

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

7 Citations (Scopus)

Abstract

H.264 is the state-of-the-art in modern video compression standards. Its extremely high compression ratio meets the requirements the video communication between portable devices. Since the power is limited in portable devices, the huge computation of H.264 is a critical problem for hardware design. According to the human visual system (HVS) research, human vision is only able to focus on one area in a frame, which is defined as region-of-interest (ROI). In most cases, human face attracts the most attention of the device user. This phenomenon gives a chance to code all macroblocks unequally. In this work, the ROI is detected with an encoder-oriented fast algorithm, using chrominance and texture contrast features. After the ROI is detected, the encoder will allocated the coding parameters respectively in ROI and non-ROI. As a result, it keeps fine quality in ROI, saves much throughput in non-ROI, and greatly reduces the computation. The ROI detector and the encoder are also designed to be decoding-friendly and hardware-friendly.

Original languageEnglish
Title of host publicationProceedings of 2009 5th International Colloquium on Signal Processing and Its Applications, CSPA 2009
Pages233-237
Number of pages5
DOIs
Publication statusPublished - 2009
Event2009 5th International Colloquium on Signal Processing and Its Applications, CSPA 2009 - Kuala Lumpur
Duration: 2009 Mar 62009 Mar 8

Other

Other2009 5th International Colloquium on Signal Processing and Its Applications, CSPA 2009
CityKuala Lumpur
Period09/3/609/3/8

Keywords

  • Dynamical parameter allocation
  • H.264/AVC
  • Human visual system (HVS)
  • Region-of-interest (ROI)
  • Skin color

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing

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