基于DaVinci技术的视频压缩传输系统设计  被引量:2

Design of video compression transmission system based on DaVinci technology

在线阅读下载全文

作  者:刘森 LIU Sen(Department of Film and Animation,Xi’an Academy of Fine Arts,Xi’an 710065,China)

机构地区:[1]西安美术学院影视动画系,陕西西安710065

出  处:《电子设计工程》2021年第19期184-188,共5页Electronic Design Engineering

基  金:陕西省教育厅2020年度一般专项科学研究计划(20JK0258)。

摘  要:随着视频制作的清晰度、艺术效果需求的迅速发展,影视素材采集的视频信号数据量大幅增加,而在传输带宽紧张的条件下,提高压缩效率是一种有效的方法。文中在深入分析了H.264视频压缩标准后,应用改进的帧间预测搜索算法,详细阐述了该系统的信号压缩方案及实现过程。以DSP与ARM组合作为硬件处理平台,基于DaVinci系列处理器TMS320DM365和必要的外围电路,在Linux系统下设计编写信号压缩算法,实现了一种从摄像头视频采集到网络传输的解决方案。仿真测试结果表明,该系统显示效果较优,所需设备较少,经实际与同样环境下的H.264压缩标准系统对比,通过网络传输的平均时延有效降低了约30 ms,可以满足视频素材采集工作的需求。With the rapid development of the demand for clarity and artistic effects of video production,the amount of video signal data collected by film and television footage has increased significantly,and under the condition of tight transmission bandwidth,improving compression efficiency is an effective method.After in⁃depth analysis of the H.264 video compression standard,the improved inter⁃frame prediction search algorithm is applied to elaborate the signal compression scheme and implementation process of the system.With the combination of DSP and ARM as the hardware processing platform,based on the DaVinci series processor TMS320DM365 and necessary peripheral circuits,a signal compression algorithm is designed and written under the Linux system,and a solution from camera video capture to network transmission is realized.The simulation test results show that the system has good display effect and requires less equipment.Compared with the H.264 compression standard system under the same environment,the average delay of transmission through the network is effectively reduced by about 30 ms,which can meet the demand for collection work of video material.

关 键 词:视频压缩 DAVINCI 帧间预测 运动矢量 视频传输 

分 类 号:TN912[电子电信—通信与信息系统]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象