基于运动矢量分类的视频编码残差信号传输优化

L. Raja, R. Swaminathan, D. K. Sharma, R. Regin, S. R, D. Babu
{"title":"基于运动矢量分类的视频编码残差信号传输优化","authors":"L. Raja, R. Swaminathan, D. K. Sharma, R. Regin, S. R, D. Babu","doi":"10.1109/I-SMAC52330.2021.9640930","DOIUrl":null,"url":null,"abstract":"Figuring interpolated images is an exemplary issue in picture and video preparation. It is an essential advancement in various applications, such as frame rate conversion, temporal upsampling for producing moderate movement video, and picture transforming, just as virtual view blend. Standard ways to deal with figuring interpolated frames in a video grouping require precise pixel correspondences between pictures. Customary answers for picture interjection initially register correspondences (for the most part utilizing optical stream or stereo techniques), trailed by correspondence-based picture distorting. Because of characteristic ambiguities in figuring such correspondences, most strategies are vigorously subject to computationally costly worldwide improvement and require extensive parameter tuning. In this proposed technique, a new complication motion with a low vector dispensation procedure at the end side is suggested for motion-compensated video vector frame interpolation or frame rate up-conversion. Generally, it is possible to detect the problems of broken edges and distorted arrangement difficulties in a frame interpolation through orderly refining motion vectors on various block sizes. Investigational consequences show that this proposed organization’s visual superiority is improved and is also rugged, even in video sequences containing fast motions and difficult sections.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimize the Residual Signal Transmission Based on Moving Vector Classification for Video Coding\",\"authors\":\"L. Raja, R. Swaminathan, D. K. Sharma, R. Regin, S. R, D. Babu\",\"doi\":\"10.1109/I-SMAC52330.2021.9640930\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Figuring interpolated images is an exemplary issue in picture and video preparation. It is an essential advancement in various applications, such as frame rate conversion, temporal upsampling for producing moderate movement video, and picture transforming, just as virtual view blend. Standard ways to deal with figuring interpolated frames in a video grouping require precise pixel correspondences between pictures. Customary answers for picture interjection initially register correspondences (for the most part utilizing optical stream or stereo techniques), trailed by correspondence-based picture distorting. Because of characteristic ambiguities in figuring such correspondences, most strategies are vigorously subject to computationally costly worldwide improvement and require extensive parameter tuning. In this proposed technique, a new complication motion with a low vector dispensation procedure at the end side is suggested for motion-compensated video vector frame interpolation or frame rate up-conversion. Generally, it is possible to detect the problems of broken edges and distorted arrangement difficulties in a frame interpolation through orderly refining motion vectors on various block sizes. Investigational consequences show that this proposed organization’s visual superiority is improved and is also rugged, even in video sequences containing fast motions and difficult sections.\",\"PeriodicalId\":178783,\"journal\":{\"name\":\"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I-SMAC52330.2021.9640930\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SMAC52330.2021.9640930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

计算插值图像是图像和视频准备中的一个示例性问题。它是各种应用的重要进步,例如帧率转换,用于制作适度运动视频的时间上采样,以及图像转换,就像虚拟视图混合一样。处理视频分组中插值帧的标准方法要求图像之间具有精确的像素对应关系。图像插入的习惯答案首先注册对应(大部分使用光流或立体技术),然后是基于对应的图像失真。由于在计算这种对应关系时存在特征模糊性,因此大多数策略都需要在全球范围内进行计算成本高昂的改进,并且需要大量的参数调整。在该技术中,提出了一种新的复杂运动,在端侧采用低矢量分配程序,用于运动补偿视频矢量帧插值或帧率上转换。一般来说,通过对不同块大小的运动向量进行有序的细化,可以检测到帧插值中的断边和畸变排列困难问题。调查结果表明,即使在包含快速运动和困难部分的视频序列中,该组织的视觉优势也得到了改善,并且坚固耐用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimize the Residual Signal Transmission Based on Moving Vector Classification for Video Coding
Figuring interpolated images is an exemplary issue in picture and video preparation. It is an essential advancement in various applications, such as frame rate conversion, temporal upsampling for producing moderate movement video, and picture transforming, just as virtual view blend. Standard ways to deal with figuring interpolated frames in a video grouping require precise pixel correspondences between pictures. Customary answers for picture interjection initially register correspondences (for the most part utilizing optical stream or stereo techniques), trailed by correspondence-based picture distorting. Because of characteristic ambiguities in figuring such correspondences, most strategies are vigorously subject to computationally costly worldwide improvement and require extensive parameter tuning. In this proposed technique, a new complication motion with a low vector dispensation procedure at the end side is suggested for motion-compensated video vector frame interpolation or frame rate up-conversion. Generally, it is possible to detect the problems of broken edges and distorted arrangement difficulties in a frame interpolation through orderly refining motion vectors on various block sizes. Investigational consequences show that this proposed organization’s visual superiority is improved and is also rugged, even in video sequences containing fast motions and difficult sections.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信