An Adaptive Model Parameters Prediction Mechanism for LCU-Level Rate Control

  • Zeqi Feng
  • Pengyu LiuEmail author
  • Kebin JiaEmail author
  • Kun Duan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)


In this paper, an adaptive model parameters prediction mechanism is proposed to take the place of parameter updating method based on the experience value in HEVC. And, normalized mutual information is exploited to guide the model parameters of α and β prediction. Experimental results show that the proposed algorithm controls the rate error within 0.1%. Compared with HM16.9, it further improves average 0.03% bit rate accuracy. Meanwhile, the proposed algorithm yields average 1.10% BDBR reduction and 0.05 dB BDPSNR enhancement without introducing additional computation. And it demonstrates less bit rate fluctuation, which achieves better adaptability for HEVC in real-time transmission.


HEVC Rate control Model parameters 



This paper is supported by the Project for the National Natural Science Foundation of China under Grants No. 61672064, the Beijing Natural Science Foundation under Grant No. 4172001, the China Postdoctoral Science Foundation under Grants No. 2016T90022, 2015M580029, the Science and Technology Project of Beijing Municipal Education Commission under Grants No. KZ201610005007, Beijing Municipal Education Committee Science Foundation under Grants No. KM201810005030, and Beijing Laboratory of Advanced Information Networks under Grants No. 040000546617002, Beijing Municipal Communications Commission Science and Technology Project under Grants No. 2017058.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Faculty of Information TechnologyBeijing University of TechnologyBeijingChina
  2. 2.Beijing Laboratory of Advanced Information NetworksBeijingChina
  3. 3.Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing University of TechnologyBeijingChina

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