Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24–25, 2019, Proceedings

Research Article

Reinforcement Learning for HEVC Screen Content Intra Coding on Heterogeneous Mobile Devices

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  • @INPROCEEDINGS{10.1007/978-3-030-32388-2_62,
        author={Yuanyuan Xu and Quanping Zeng},
        title={Reinforcement Learning for HEVC Screen Content Intra Coding on Heterogeneous Mobile Devices},
        proceedings={Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24--25, 2019, Proceedings},
        proceedings_a={MLICOM},
        year={2019},
        month={10},
        keywords={Screen content coding Coding mode decision Reinforcement learning},
        doi={10.1007/978-3-030-32388-2_62}
    }
    
  • Yuanyuan Xu
    Quanping Zeng
    Year: 2019
    Reinforcement Learning for HEVC Screen Content Intra Coding on Heterogeneous Mobile Devices
    MLICOM
    Springer
    DOI: 10.1007/978-3-030-32388-2_62
Yuanyuan Xu1,*, Quanping Zeng1
  • 1: Hohai University
*Contact email: yuanyuan_xu@hhu.edu.cn

Abstract

Intra coding of HEVC screen content coding has to evaluate HEVC intra coding modes and additional modes for screen contents, which poses a challenge for coding such a content on mobile devices. Furthermore, the heterogeneous mobile devices have varying complexity requirements. In this paper, a flexible screen content intra coding scheme is proposed, which can trade between encoding complexity and rate-distortion performance degradation via reinforcement learning (RL). Through the design of states, actions, and more importantly, the reward function for RL, the proposed scheme can learn a flexible coding policy offline. Experimental results show the effectiveness of the proposed scheme.