arrow
返回

Complexity Control Based on a Fast Coding Unit Decision Method in the HEVC Video Coding Standard

delete2016-04-01
delete36
delete
OA
AI
A
Amaya Jiménez-Moreno
E
Eduardo Martínez-Enríquez *
F
Fernando Díaz-de-María *
DOI:10.1109/TMM.2016.2524995delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
The emerging high-efficiency video coding standard achieves higher coding efficiency than previous standards by virtue of a set of new coding tools such as the quadtree coding structure. In this novel structure, the pixels are organized into coding units (CU), prediction units, and transform units, the sizes of which can be optimized at every level following a tree configuration. These tools allow highly flexible data representation; however, they incur a very high computational complexity. In this paper, we propose an effective complexity control (CC) algorithm based on a hierarchical approach. An early termination condition is defined at every CU size to determine whether subsequent CU sizes should be explored. The actual encoding times are also considered to satisfy the target complexity in real time. Moreover, all parameters of the algorithm are estimated on the fly to adapt its behavior to the video content, the encoding configuration, and the target complexity over time. The experimental results prove that our proposal is able to achieve a target complexity reduction of up to 60% with respect to full exploration, with notable accuracy and limited losses in coding performance. It was compared with a state-of-the-art CC method and shown to achieve a significantly better trade-off between coding complexity and efficiency as well as higher accuracy in reaching the target complexity. Furthermore, a comparison with a state-of-the-art complexity reduction method highlights the advantages of our CC framework. Finally, we show that the proposed method performs well when the target complexity varies over time.
Keyword:
Complexity control (CC)
fast coding unit decision
high efficiency video coding (HEVC)
on the fly estimation
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Transactions on Multimedia 封面图
IEEE Transactions on Multimedia
IF:
9.7
论文数:
4.5K
被引数:
2.4W

机构

U
Universidad Carlos III de Madrid
学者数:
5.5K
论文数: 5.7K
被引数: 4.5K
C
consejo superior de investigaciones cientificas (csic)
学者数:
8.8W
论文数: 8.5W
被引数: 125
引用论文

引用论文

err分享
err收藏
Structural, optical and magnetic properties of Cu and V co-doped ZnO nanoparticles
err2013-01-01
err0
PREAI
errHuilian Liu; Xin Cheng; Hongbo Liu; Jinghai Yang; Yang Liu; Xiaoyan Liu; Ming Gao; Maobin Wei; Xu Zhang; Yuhong Jiang
err分享
err收藏
学者 查看更多内容