Complexity Control of H.264/AVC Based on Mode-Conditional Cost Probability Distributions

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.

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