Complexity control of H.264/AVC based on mode-conditional cost probability distributions

  • Authors:

  • Chaminda Sampath Kannangara;lain E. Richardson;Maja Bystrom;Yafan Zhao

  • Affiliations:

  • School of Engineering, The Robert Gordon University, Schoolhill, Aberdeen, AB, UK;School of Engineering, The Robert Gordon University, Schoolhill, Aberdeen, AB, UK;Department of Electrical and Computer Engineering, Boston University, Boston, MA;School of Engineering, The Robert Gordon University, Schoolhill, Aberdeen, AB, UK

  • Venue:
  • IEEE Transactions on Multimedia - Special section on communities and media computing
  • Year:
  • 2009

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Abstract

A computational complexity control algorithm is proposed for an H.264 encoder running on a processor/power constrained platform. This new computational complexity control algorithm is based on a macroblock mode prediction algorithm that employs a Bayesian framework for accurate early skip decision. Complexity control is achieved by relaxing the Bayesian maximum-likelihood (ML) criterion in order to match the mode decision threshold to a target complexity level. A feedback algorithm is used to maintain the performance of the algorithm with respect to achieving an average target complexity level, reducing frame by frame complexity variance and optimizing rate-distortion performance. Experimental results show that this algorithm can effectively control the encoding computational complexity while maintaining a good rate-distortion performance at a range of target complexity levels.