An Improvement of UMHexagonS Based on Detecting Moving Object

HONG Jia-qing; LIN Qi-wei

Chinese

您当前的位置：

首页 >

文章列表页 >

An Improvement of UMHexagonS Based on Detecting Moving Object

更新时间：2026-09-04

- An Improvement of UMHexagonS Based on Detecting Moving Object
- Vol. 30, Issue 9, Pages: 126-128(2013)
- 作者机构：
  
  华侨大学机构信息科学与工程学院,福建,泉州,362021
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013
- 稿件说明：
移动端阅览
洪佳庆, 林其伟. 基于运动对象检测的UMHexagonS搜索算法改进[J]. 微电子学与计算机, 2013, 30(9): 126-128,132.

HONG Jia-qing, LIN Qi-wei. An Improvement of UMHexagonS Based on Detecting Moving Object[J]. 2013, 30(9): 126-128.
洪佳庆, 林其伟. 基于运动对象检测的UMHexagonS搜索算法改进[J]. 微电子学与计算机, 2013, 30(9): 126-128,132. DOI：

HONG Jia-qing, LIN Qi-wei. An Improvement of UMHexagonS Based on Detecting Moving Object[J]. 2013, 30(9): 126-128. DOI：

摘要

在H.264精细可分级编码中，针对减少运动估计时间，本文提出一种基于运动对象检测的UM Hexagon S搜索算法改进.首先，根据运动对象检测区分出运动区域和背景区域，对不同的区域采用不用的搜索算法;其次，利用两次菱形模版替换原来的5×5螺旋搜索，减少了50%的搜索点数，且能提前结束搜索.实验结果表明，改进后的算法，在保证图像质量基本不变的前提下，运动估计时间减少10%~40%.

Abstract

In FGS video coding

in order to reduce the time of motion estimation

this paper proposed an improvement algorithm of UMHexagonS

which is based on detecting moving object.First

distinguish between motion region and background according to the motion object detection

use different search algorithm in different areas.Then

uses two diamond template replace the original 5×5 spiral search

decreases 50% of search points

can terminate search early.The experiment results show that the improved algorithm in the premise of image quality can reduce 10%~40% of the motion estimation time.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on the design of blockchain-based AI-generated content traceability framework

Monte carlo analysis of V-layout trench SiC neutron detector

Microservices anomaly detection based on the correlation of monitoring metrics

A high-efficiency charge pump for ultra-low voltage boost systems

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰