基于学习模型的3D-HEVC提前Merge模式终止算法

李跃; 杨高波; 丁湘陵; 朱亚培

doi:10.11959/j.issn.1000-436x.2019165

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基于学习模型的3D-HEVC提前Merge模式终止算法

学术论文 | 更新时间：2024-06-05

- 基于学习模型的3D-HEVC提前Merge模式终止算法
- Early Merge mode decision algorithm for 3D-HEVC based on learning model
- 通信学报 2019年40卷第7期页码：104-113
- 作者机构：
  
  1. 南华大学计算机学院，湖南衡阳 421001
  2. 湖南大学信息科学与工程学院，湖南长沙 410082
  3. 湖南科技大学计算机科学与工程学院，湖南湘潭 411201
  4. 衡阳师范学院物理与电子学院，湖南衡阳 421002
- 作者简介：
  
  [ "李跃（1988- ），男，湖南衡阳人，博士，南华大学讲师，主要研究方向为 HEVC、3D-HEVC、VVC编码优化等。" ]
  [ "杨高波（1974- ），男，湖南岳阳人，博士，湖南大学教授、博士生导师，主要研究方向为图像/视频信号处理、多媒体通信、数字媒体内容安全等。" ]
  [ "丁湘陵（1981- ），男，湖南株洲人，博士，湖南科技大学副教授，主要研究方向为视频信息安全、图像处理等。" ]
  [ "朱亚培（1988- ），女，河南驻马店人，衡阳师范学院讲师，主要研究方向为图像/视频压缩等。" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2018YFB1003205);国家自然科学基金资助项目(61572183)
- DOI：10.11959/j.issn.1000-436x.2019165
  中图分类号： TN919.8
- 网络出版日期：2019-07，
  
  纸质出版日期：2019-07-25
- 稿件说明：
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李跃, 杨高波, 丁湘陵, 等. 基于学习模型的3D-HEVC提前Merge模式终止算法[J]. 通信学报, 2019,40(7):104-113.

Yue LI, Gaobo YANG, Xiangling DING, et al. Early Merge mode decision algorithm for 3D-HEVC based on learning model[J]. Journal on communications, 2019, 40(7): 104-113.
李跃, 杨高波, 丁湘陵, 等. 基于学习模型的3D-HEVC提前Merge模式终止算法[J]. 通信学报, 2019,40(7):104-113. DOI： 10.11959/j.issn.1000-436x.2019165.

Yue LI, Gaobo YANG, Xiangling DING, et al. Early Merge mode decision algorithm for 3D-HEVC based on learning model[J]. Journal on communications, 2019, 40(7): 104-113. DOI： 10.11959/j.issn.1000-436x.2019165.

摘要

作为高效视频编码（HEVC）的扩展，3D-HEVC标准有效地提高了3D视频的压缩效率，但是也带来了很高的编码计算复杂度。为了显著地降低3D-HEVC编码复杂度，提出了一种提前Merge模式终止算法。首先，提取 Merge 模式编码后的残差信号作为特征信息；然后，根据当前编码帧内已经编码的编码单元（CU）的最优Merge模式残差信号建立学习模型；最后，提取当前CU的Merge模式的残差信号，并且利用学习模型预测Merge模式是否为最优模式。实验结果表明，提出的提前Merge模式终止算法分别将3D-HEVC纹理视点和深度图编码的时间降低了41.9%和24.3%，且编码性能的降低几乎可忽略不计。相较于现有的提前Merge模式算法，提出的提前Merge模式终止算法能进一步降低3D-HEVC的编码时间，并且设计简单，易于集成到3D-HEVC测试模型。

Abstract

3D-high efficiency video coding (3D-HEVC) standard is an extension of HEVC.Though 3D-HEVC effectively improves the compression efficiency of 3D video

it also brings huge computational complexity.To greatly reduce the 3D-HEVC coding complexity

an early Merge mode decision approach was proposed.The residual signal that encoded by the Merge mode was firstly extracted as feature information.A learning model was established in terms of the residual signals of the coding unit (CU) in current frame that used early Merge mode as the optimal mode.Finally

the residual signal was extracted for the Merge mode of current CU

and the learning model was used to predict whether the Merge mode was the optimal mode or not.Experimental results show that the proposed early Merge mode decision approach reduces the coding times of 3D-HEVC texture views and depth maps about 41.9% and 24.3%

respectively

and the coding performance degradation is almost negligible.Compared with existing early Merge mode decision approaches

the proposed approach further reduces the coding time

and can be easily integrated into the 3D-HEVC test model due to its design simplicity.

关键词

Keywords

references

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