Long-term prediction for hierarchical-B-picture-based coding of video with repeated shots
被引:0
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作者:
Xu-guang Zuo
论文数: 0引用数: 0
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机构:Zhejiang University,Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Institute of Information and Communication Engineering
Xu-guang Zuo
Lu Yu
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h-index: 0
机构:Zhejiang University,Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Institute of Information and Communication Engineering
Lu Yu
机构:
[1] Zhejiang University,Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), Institute of Information and Communication Engineering
来源:
Frontiers of Information Technology & Electronic Engineering
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2018年
/
19卷
关键词:
High Efficiency Video Coding (HEVC);
Long-term temporal correlation;
Long-term prediction;
Hierarchical B-picture structure;
TN919.8;
D O I:
暂无
中图分类号:
学科分类号:
摘要:
The latest video coding standard High Efficiency Video Coding (HEVC) can achieve much higher coding efficiency than previous video coding standards. Particularly, by exploiting the hierarchical B-picture prediction structure, temporal redundancy among neighbor frames is eliminated remarkably well. In practice, videos available to consumers usually contain many repeated shots, such as TV series, movies, and talk shows. According to our observations, when these videos are encoded by HEVC with the hierarchical B-picture structure, the temporal correlation in each shot is well exploited. However, the long-term correlation between repeated shots has not been used. We propose a long-term prediction (LTP) scheme to use the long-term temporal correlation between correlated shots in a video. The long-term reference (LTR) frames of a source video are chosen by clustering similar shots and extracting the representative frames, and a modified hierarchical B-picture coding structure based on an LTR frame is introduced to support long-term temporal prediction. An adaptive quantization method is further designed for LTR frames to improve the overall video coding efficiency. Experimental results show that up to 22.86% coding gain can be achieved using the new coding scheme.
机构:
Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Yan, Haoran
Qin, Yi
论文数: 0引用数: 0
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机构:
Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Qin, Yi
Xiang, Sheng
论文数: 0引用数: 0
h-index: 0
机构:
Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Xiang, Sheng
Wang, Yi
论文数: 0引用数: 0
h-index: 0
机构:
Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
Wang, Yi
Chen, Haizhou
论文数: 0引用数: 0
h-index: 0
机构:
Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266061, Peoples R ChinaChongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
机构:
China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
Minist Agr, Key Lab Agr Informat Acquisit Technol, Beijing 100083, Peoples R China
Beijing Engn & Technol Res Ctr Internet Things Ag, Beijing 100083, Peoples R ChinaChina Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
Liu, Yeqi
Zhang, Qian
论文数: 0引用数: 0
h-index: 0
机构:
China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
Minist Agr, Key Lab Agr Informat Acquisit Technol, Beijing 100083, Peoples R China
Beijing Engn & Technol Res Ctr Internet Things Ag, Beijing 100083, Peoples R ChinaChina Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
Zhang, Qian
Song, Lihua
论文数: 0引用数: 0
h-index: 0
机构:
China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
Minist Agr, Key Lab Agr Informat Acquisit Technol, Beijing 100083, Peoples R China
Beijing Engn & Technol Res Ctr Internet Things Ag, Beijing 100083, Peoples R ChinaChina Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
Song, Lihua
Chen, Yingyi
论文数: 0引用数: 0
h-index: 0
机构:
China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
Minist Agr, Key Lab Agr Informat Acquisit Technol, Beijing 100083, Peoples R China
Beijing Engn & Technol Res Ctr Internet Things Ag, Beijing 100083, Peoples R China
China Agr Univ, Natl Innovat Ctr Digital Fishery, Beijing 100083, Peoples R ChinaChina Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China