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Self-learning residual model for fast intra CU size decision in 3D-HEVC

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成果类型:
期刊论文
作者:
Li, Yue;Zhu, Ningbo;Yang, Gaobo*;Zhu, Yapei;Ding, Xiangling
通讯作者:
Yang, Gaobo
作者机构:
[Li, Yue] Univ South China, Comp Sch, Hengyang 421001, Peoples R China.
[Yang, Gaobo; Li, Yue; Zhu, Ningbo] Hunan Univ, Sch Informat Sci & Engn, Changsha 410082, Hunan, Peoples R China.
[Zhu, Yapei] Hengyang Normal Univ, Fac Phys & Elect Informat Sci, Hengyang 421002, Peoples R China.
[Ding, Xiangling] Hunan Univ Sci & Technol, Sch Comp Sci & Engn, Xiangtan 411201, Peoples R China.
通讯机构:
[Yang, Gaobo] H
Hunan Univ, Sch Informat Sci & Engn, Changsha 410082, Hunan, Peoples R China.
语种:
英文
关键词:
3D high efficiency video coding;Self-learning;Fast intra coding;CU size decision;Residual signal
期刊:
Signal Processing: Image Communication
ISSN:
0923-5965
年:
2020
卷:
80
页码:
115660
基金类别:
National Key Research and Development Plan of China [2018YFB1003205]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [61572183, 61572177]
机构署名:
本校为其他机构
院系归属:
物理与电子工程学院
摘要:
As an extension of the High Efficiency Video Coding (HEVC) standard, 3D-HEVC requires to encode multiple texture views and depth maps, which inherits the same quad-tree coding structure as HEVC. Due to the distinct properties of texture views and depth maps, existing fast intra prediction approaches were presented for the coding of texture views and depth maps, respectively. To further reduce the coding complexity of 3D-HEVC, a self-learning residual model-based fast coding unit (CU) size decision approach is proposed for the intra coding of both texture views and depth maps. Residual signal, ...

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