基于视频场景分析的改进运动矢量估计视频错误隐藏方法

S. M. Zabihi, Hossein Ghanei-Yakhdan, N. Mehrshad
{"title":"基于视频场景分析的改进运动矢量估计视频错误隐藏方法","authors":"S. M. Zabihi, Hossein Ghanei-Yakhdan, N. Mehrshad","doi":"10.22068/IJEEE.16.4.461","DOIUrl":null,"url":null,"abstract":"In order to enhance the accuracy of the motion vector (MV) estimation and also reduce the error propagation issue during the estimation, in this paper, a new adaptive error concealment (EC) approach is proposed based on the information extracted from the video scene. In this regard, the motion information of the video scene around the degraded MB is first analyzed to estimate the motion type of the degraded MB. If the neighboring MBs possess uniform motion, the degraded MB imitates the behavior of neighboring MBs by choosing the MV of the collocated MB. Otherwise, the lost MV is estimated through the second proposed EC technique (i.e., IOBMA). In the IOBMA, unlike the conventional boundary matching criterion-based EC techniques, not only each boundary distortion is evaluated regarding both the luminance and the chrominance components of the boundary pixels, but also the total boundary distortion corresponding to each candidate MV is calculated as the weighted average of the available boundary distortions. Compared with the state-of-the-art EC techniques, the simulation results indicate the superiority of the proposed EC approach in terms of both the objective and subjective quality assessments.","PeriodicalId":39055,"journal":{"name":"Iranian Journal of Electrical and Electronic Engineering","volume":"16 1","pages":"461-473"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Improved Motion Vector Estimation Approach for Video Error Concealment Based on the Video Scene Analysis\",\"authors\":\"S. M. Zabihi, Hossein Ghanei-Yakhdan, N. Mehrshad\",\"doi\":\"10.22068/IJEEE.16.4.461\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to enhance the accuracy of the motion vector (MV) estimation and also reduce the error propagation issue during the estimation, in this paper, a new adaptive error concealment (EC) approach is proposed based on the information extracted from the video scene. In this regard, the motion information of the video scene around the degraded MB is first analyzed to estimate the motion type of the degraded MB. If the neighboring MBs possess uniform motion, the degraded MB imitates the behavior of neighboring MBs by choosing the MV of the collocated MB. Otherwise, the lost MV is estimated through the second proposed EC technique (i.e., IOBMA). In the IOBMA, unlike the conventional boundary matching criterion-based EC techniques, not only each boundary distortion is evaluated regarding both the luminance and the chrominance components of the boundary pixels, but also the total boundary distortion corresponding to each candidate MV is calculated as the weighted average of the available boundary distortions. Compared with the state-of-the-art EC techniques, the simulation results indicate the superiority of the proposed EC approach in terms of both the objective and subjective quality assessments.\",\"PeriodicalId\":39055,\"journal\":{\"name\":\"Iranian Journal of Electrical and Electronic Engineering\",\"volume\":\"16 1\",\"pages\":\"461-473\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iranian Journal of Electrical and Electronic Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22068/IJEEE.16.4.461\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Electrical and Electronic Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22068/IJEEE.16.4.461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0

摘要

为了提高运动矢量估计的精度,同时减少估计过程中的误差传播问题,本文提出了一种基于视频场景信息提取的自适应误差隐藏方法。为此,首先分析降级MB周围视频场景的运动信息,估计降级MB的运动类型。如果相邻MB具有均匀运动,则降级MB通过选择并置MB的MV来模仿相邻MB的行为。否则,通过第二种提出的EC技术(即IOBMA)估计丢失的MV。在IOBMA中,与传统的基于边界匹配准则的EC技术不同,它不仅根据边界像素的亮度和色度分量评估每个边界畸变,而且计算每个候选MV对应的总边界畸变作为可用边界畸变的加权平均值。仿真结果表明,该方法在客观质量评价和主观质量评价两方面都具有较好的优越性。
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
An Improved Motion Vector Estimation Approach for Video Error Concealment Based on the Video Scene Analysis
In order to enhance the accuracy of the motion vector (MV) estimation and also reduce the error propagation issue during the estimation, in this paper, a new adaptive error concealment (EC) approach is proposed based on the information extracted from the video scene. In this regard, the motion information of the video scene around the degraded MB is first analyzed to estimate the motion type of the degraded MB. If the neighboring MBs possess uniform motion, the degraded MB imitates the behavior of neighboring MBs by choosing the MV of the collocated MB. Otherwise, the lost MV is estimated through the second proposed EC technique (i.e., IOBMA). In the IOBMA, unlike the conventional boundary matching criterion-based EC techniques, not only each boundary distortion is evaluated regarding both the luminance and the chrominance components of the boundary pixels, but also the total boundary distortion corresponding to each candidate MV is calculated as the weighted average of the available boundary distortions. Compared with the state-of-the-art EC techniques, the simulation results indicate the superiority of the proposed EC approach in terms of both the objective and subjective quality assessments.
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
Iranian Journal of Electrical and Electronic Engineering
Iranian Journal of Electrical and Electronic Engineering Engineering-Electrical and Electronic Engineering
CiteScore
1.70
自引率
0.00%
发文量
13
审稿时长
12 weeks
期刊最新文献
Robust Operation Planning With Participation of Flexibility Resources Both on Generation and Demand Sides Under Uncertainty of Wind-based Generation Units A Novel Droop-based Control Strategy for Improving the Performance of VSC-MTDC Systems in Post-Contingency Conditions Securing Reliability Constrained Technology Combination for Isolated Micro-Grid Using Multi-Agent Based Optimization View-Invariant and Robust Gait Recognition Using Gait Energy Images of Leg Region and Masking Altered Sections Multiple Electricity Markets Competitiveness Undergoing Symmetric and Asymmetric Renewables Development Policies
×
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