基于3D-HEVC的深度图内预测复杂度降低算法

G. Sanchez, Mário Saldanha, Gabriel Balota, B. Zatt, M. Porto, L. Agostini
{"title":"基于3D-HEVC的深度图内预测复杂度降低算法","authors":"G. Sanchez, Mário Saldanha, Gabriel Balota, B. Zatt, M. Porto, L. Agostini","doi":"10.1109/VCIP.2014.7051523","DOIUrl":null,"url":null,"abstract":"This paper proposes a complexity reduction algorithm for the depth maps intra prediction of the emerging 3D High Efficiency Video Coding standard (3D-HEVC). The 3D-HEVC introduces a new set of specific tools for the depth map coding that includes four Depth Modeling Modes (DMM) and these new features have inserted extra effort on the intra prediction. This extra effort is undesired and contributes to increasing the power consumption, which is a huge problem especially for embedded-systems. For this reason, this paper proposes a complexity reduction algorithm for the DMM 1, called Gradient-Based Mode One Filter (GMOF). This algorithm applies a filter to the borders of the encoded block and determines the best positions to evaluate the DMM 1, reducing the computational effort of DMM 1 process. Experimental analysis showed that GMOF is capable to achieve, in average, a complexity reduction of 9.8% on depth maps prediction, when evaluating under Common Test Conditions (CTC), with minor impacts on the quality of the synthesized views.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"A complexity reduction algorithm for depth maps intra prediction on the 3D-HEVC\",\"authors\":\"G. Sanchez, Mário Saldanha, Gabriel Balota, B. Zatt, M. Porto, L. Agostini\",\"doi\":\"10.1109/VCIP.2014.7051523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a complexity reduction algorithm for the depth maps intra prediction of the emerging 3D High Efficiency Video Coding standard (3D-HEVC). The 3D-HEVC introduces a new set of specific tools for the depth map coding that includes four Depth Modeling Modes (DMM) and these new features have inserted extra effort on the intra prediction. This extra effort is undesired and contributes to increasing the power consumption, which is a huge problem especially for embedded-systems. For this reason, this paper proposes a complexity reduction algorithm for the DMM 1, called Gradient-Based Mode One Filter (GMOF). This algorithm applies a filter to the borders of the encoded block and determines the best positions to evaluate the DMM 1, reducing the computational effort of DMM 1 process. Experimental analysis showed that GMOF is capable to achieve, in average, a complexity reduction of 9.8% on depth maps prediction, when evaluating under Common Test Conditions (CTC), with minor impacts on the quality of the synthesized views.\",\"PeriodicalId\":166978,\"journal\":{\"name\":\"2014 IEEE Visual Communications and Image Processing Conference\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Visual Communications and Image Processing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP.2014.7051523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Visual Communications and Image Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP.2014.7051523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24

摘要

针对新兴的3D高效视频编码标准(3D- hevc),提出了一种深度图帧内预测的复杂度降低算法。3D-HEVC为深度图编码引入了一套新的特定工具,其中包括四种深度建模模式(DMM),这些新功能为图像内预测增加了额外的工作量。这种额外的工作是不希望的,并且会增加功耗,这是一个巨大的问题,特别是对于嵌入式系统。为此,本文提出了一种dmm1的复杂度降低算法,称为基于梯度的模式一滤波器(GMOF)。该算法对编码块的边界进行滤波,确定对DMM - 1进行评估的最佳位置,减少了DMM - 1过程的计算量。实验分析表明,在通用测试条件(Common Test Conditions, CTC)下评估时,GMOF能够将深度图预测的复杂性平均降低9.8%,对合成视图的质量影响较小。
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 complexity reduction algorithm for depth maps intra prediction on the 3D-HEVC
This paper proposes a complexity reduction algorithm for the depth maps intra prediction of the emerging 3D High Efficiency Video Coding standard (3D-HEVC). The 3D-HEVC introduces a new set of specific tools for the depth map coding that includes four Depth Modeling Modes (DMM) and these new features have inserted extra effort on the intra prediction. This extra effort is undesired and contributes to increasing the power consumption, which is a huge problem especially for embedded-systems. For this reason, this paper proposes a complexity reduction algorithm for the DMM 1, called Gradient-Based Mode One Filter (GMOF). This algorithm applies a filter to the borders of the encoded block and determines the best positions to evaluate the DMM 1, reducing the computational effort of DMM 1 process. Experimental analysis showed that GMOF is capable to achieve, in average, a complexity reduction of 9.8% on depth maps prediction, when evaluating under Common Test Conditions (CTC), with minor impacts on the quality of the synthesized views.
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
A joint 3D image semantic segmentation and scalable coding scheme with ROI approach Disocclusion hole-filling in DIBR-synthesized images using multi-scale template matching Rate-distortion optimised transform competition for intra coding in HEVC Robust image registration using adaptive expectation maximisation based PCA Non-separable mode dependent transforms for intra coding in HEVC
×
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