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
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.
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