一种时空去隔行算法

T. Chong, O. Au, Tai-Wai Chan, Wing-San Chau
{"title":"一种时空去隔行算法","authors":"T. Chong, O. Au, Tai-Wai Chan, Wing-San Chau","doi":"10.1109/ICME.2005.1521407","DOIUrl":null,"url":null,"abstract":"In this paper, we proposed a spatial-temporal de-interlacing algorithm for conversion of interlaced video to progressive video. Our proposed algorithm estimates the motion trajectory of three consecutive fields interpolates the missing field along the motion trajectory. In the motion estimator, the unidirectional motion estimation and the bidirectional motion estimation processes are combined by multiple objective minimization technique. The unidirectional motion estimation estimates the motion trajectory by comparing the blocks from opposite parity fields while the bi-directional motion estimation compares blocks from the same parity fields. By combining the two motion estimations, the motion trajectory can be accurately predicted. In addition, a quality analyzer is proposed to evaluate the visual quality of the reconstructed frame, which chooses the appropriate interpolation scheme in order to provide maximum de-interlacing performance. Simulation results show the proposed algorithm has better performance over existing de-interlacing algorithm.","PeriodicalId":244360,"journal":{"name":"2005 IEEE International Conference on Multimedia and Expo","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A spatial-temporal de-interlacing algorithm\",\"authors\":\"T. Chong, O. Au, Tai-Wai Chan, Wing-San Chau\",\"doi\":\"10.1109/ICME.2005.1521407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we proposed a spatial-temporal de-interlacing algorithm for conversion of interlaced video to progressive video. Our proposed algorithm estimates the motion trajectory of three consecutive fields interpolates the missing field along the motion trajectory. In the motion estimator, the unidirectional motion estimation and the bidirectional motion estimation processes are combined by multiple objective minimization technique. The unidirectional motion estimation estimates the motion trajectory by comparing the blocks from opposite parity fields while the bi-directional motion estimation compares blocks from the same parity fields. By combining the two motion estimations, the motion trajectory can be accurately predicted. In addition, a quality analyzer is proposed to evaluate the visual quality of the reconstructed frame, which chooses the appropriate interpolation scheme in order to provide maximum de-interlacing performance. Simulation results show the proposed algorithm has better performance over existing de-interlacing algorithm.\",\"PeriodicalId\":244360,\"journal\":{\"name\":\"2005 IEEE International Conference on Multimedia and Expo\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 IEEE International Conference on Multimedia and Expo\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICME.2005.1521407\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Conference on Multimedia and Expo","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2005.1521407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

在本文中,我们提出了一种将隔行视频转换为逐行视频的时空去隔行算法。我们提出的算法估计三个连续场的运动轨迹,沿运动轨迹插值缺失的场。在运动估计器中,采用多目标最小化技术将单向运动估计和双向运动估计相结合。单向运动估计通过比较来自相反奇偶域的块来估计运动轨迹,双向运动估计通过比较来自相同奇偶域的块来估计运动轨迹。结合这两种运动估计,可以准确地预测运动轨迹。此外,提出了一个质量分析仪来评估重建帧的视觉质量,选择合适的插值方案,以提供最大的去隔行性能。仿真结果表明,该算法比现有的去隔行算法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A spatial-temporal de-interlacing algorithm
In this paper, we proposed a spatial-temporal de-interlacing algorithm for conversion of interlaced video to progressive video. Our proposed algorithm estimates the motion trajectory of three consecutive fields interpolates the missing field along the motion trajectory. In the motion estimator, the unidirectional motion estimation and the bidirectional motion estimation processes are combined by multiple objective minimization technique. The unidirectional motion estimation estimates the motion trajectory by comparing the blocks from opposite parity fields while the bi-directional motion estimation compares blocks from the same parity fields. By combining the two motion estimations, the motion trajectory can be accurately predicted. In addition, a quality analyzer is proposed to evaluate the visual quality of the reconstructed frame, which chooses the appropriate interpolation scheme in order to provide maximum de-interlacing performance. Simulation results show the proposed algorithm has better performance over existing de-interlacing algorithm.
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
期刊最新文献
Lossless image compression with tree coding of magnitude levels Maximizing the profit for cache replacement in a transcoding proxy Pre-Attentional Filtering in Compressed Video Annotation and detection of blended emotions in real human-human dialogs recorded in a call center Fast inter frame encoding based on modes pre-decision in H.264
×
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