Lossless Decoding Method of Compressed Coded Video Based on Inter-Frame Differential Background Model: Multi-Algorithm Joint Lossless Decoding

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS International Journal of Grid and High Performance Computing Pub Date : 2023-02-16 DOI:10.4018/ijghpc.318407
Lehua Hu
{"title":"Lossless Decoding Method of Compressed Coded Video Based on Inter-Frame Differential Background Model: Multi-Algorithm Joint Lossless Decoding","authors":"Lehua Hu","doi":"10.4018/ijghpc.318407","DOIUrl":null,"url":null,"abstract":"For the problems of low decoding accuracy, long decoding time, and low quality of decoded video image in the traditional lossless decoding method of compressed coded video, a lossless decoding method of compressed coded video based on inter frame difference background model is proposed. At the coding end, the inter frame difference background model is used to extract the single frame video image, and the mixed coding method is used to compress the video losslessly. At the decoding side, the CS-SOMP (compressive sensing-synchronous orthogonal matching pursuit algorithm) joint reconstruction algorithm is composed of synchronous orthogonal matching pursuit algorithm (SOMP) and K-SVD (kernel singular value decomposition) algorithm to losslessly decode the compressed encoded video. The simulation results show that the lossless decoding method based on the inter frame difference background model has higher accuracy, shorter decoding time, and ensures the quality of the decoded video image.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"171 1","pages":"1-13"},"PeriodicalIF":0.6000,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Grid and High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijghpc.318407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

For the problems of low decoding accuracy, long decoding time, and low quality of decoded video image in the traditional lossless decoding method of compressed coded video, a lossless decoding method of compressed coded video based on inter frame difference background model is proposed. At the coding end, the inter frame difference background model is used to extract the single frame video image, and the mixed coding method is used to compress the video losslessly. At the decoding side, the CS-SOMP (compressive sensing-synchronous orthogonal matching pursuit algorithm) joint reconstruction algorithm is composed of synchronous orthogonal matching pursuit algorithm (SOMP) and K-SVD (kernel singular value decomposition) algorithm to losslessly decode the compressed encoded video. The simulation results show that the lossless decoding method based on the inter frame difference background model has higher accuracy, shorter decoding time, and ensures the quality of the decoded video image.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于帧间差分背景模型的压缩编码视频无损解码方法:多算法联合无损解码
针对传统的压缩编码视频无损解码方法存在解码精度低、解码时间长、解码后视频图像质量低等问题,提出了一种基于帧间差分背景模型的压缩编码视频无损解码方法。在编码端,采用帧间差分背景模型提取单帧视频图像,采用混合编码方法对视频进行无损压缩。在解码端,CS-SOMP(压缩感知-同步正交匹配追踪算法)联合重构算法由同步正交匹配追踪算法(SOMP)和K-SVD(核奇异值分解)算法组成,对压缩后的编码视频进行无损解码。仿真结果表明,基于帧间差分背景模型的无损解码方法具有更高的解码精度,更短的解码时间,保证了解码后视频图像的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
1.70
自引率
10.00%
发文量
24
期刊最新文献
A Potent View on the Effects of E-Learning Pre-Cutoff Value Calculation Method for Accelerating Metric Space Outlier Detection A Security Method for Cloud Storage Using Data Classification An Energy-Efficient Multi-Channel Design for Distributed Wireless Sensor Networks On Allocation Algorithms for Manycore Systems With Network on Chip
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1