基于MCMC的x265编码器高效参数选择模型

Yan Huang, Li Song, Rong Xie, Zhengyi Luo, Xiangwen Wang
{"title":"基于MCMC的x265编码器高效参数选择模型","authors":"Yan Huang, Li Song, Rong Xie, Zhengyi Luo, Xiangwen Wang","doi":"10.1109/ISCAS.2018.8351034","DOIUrl":null,"url":null,"abstract":"As an open-source and computationally efficient High Efficiency Video Coding (HEVC) encoder, x265 has been gaining increasing popularity in video applications. x265 provides numerous encoding parameters in view of flexibility. However, proper and efficient setting of parameters often becomes a great challenge in practice. In this paper, we deeply investigate the influence of x265 parameters based on the Slow preset and pick out important parameters in terms of efficiency and complexity. Then a Markov Chain Monte Carlo (MCMC) based algorithm is proposed for efficient parameter adaptation at the target encoding time. This paper shows that carefully selected low-complexity encoding configurations can achieve the coding efficiency comparable to that of high-complexity ones. Specifically, average 26.72% encoding time reduction can be achieved while maintaining similar Rate Distortion (RD) performance to x265 presets using the proposed algorithm.","PeriodicalId":6569,"journal":{"name":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","volume":"17 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An MCMC based Efficient Parameter Selection Model for x265 Encoder\",\"authors\":\"Yan Huang, Li Song, Rong Xie, Zhengyi Luo, Xiangwen Wang\",\"doi\":\"10.1109/ISCAS.2018.8351034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As an open-source and computationally efficient High Efficiency Video Coding (HEVC) encoder, x265 has been gaining increasing popularity in video applications. x265 provides numerous encoding parameters in view of flexibility. However, proper and efficient setting of parameters often becomes a great challenge in practice. In this paper, we deeply investigate the influence of x265 parameters based on the Slow preset and pick out important parameters in terms of efficiency and complexity. Then a Markov Chain Monte Carlo (MCMC) based algorithm is proposed for efficient parameter adaptation at the target encoding time. This paper shows that carefully selected low-complexity encoding configurations can achieve the coding efficiency comparable to that of high-complexity ones. Specifically, average 26.72% encoding time reduction can be achieved while maintaining similar Rate Distortion (RD) performance to x265 presets using the proposed algorithm.\",\"PeriodicalId\":6569,\"journal\":{\"name\":\"2018 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"volume\":\"17 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCAS.2018.8351034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2018.8351034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

作为一种开源且计算效率高的高效视频编码(HEVC)编码器,x265在视频应用中越来越受欢迎。考虑到灵活性,X265提供了许多编码参数。然而,在实际应用中,如何合理有效地设置参数往往是一个巨大的挑战。在本文中,我们深入研究了基于Slow预设的x265参数的影响,并从效率和复杂度方面挑选出重要的参数。在此基础上,提出了一种基于马尔可夫链蒙特卡罗(MCMC)的目标编码时间参数自适应算法。本文表明,通过精心选择低复杂度的编码结构,可以实现与高复杂度编码结构相当的编码效率。具体来说,使用该算法可以在保持与x265预设相似的率失真(RD)性能的同时,平均减少26.72%的编码时间。
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 MCMC based Efficient Parameter Selection Model for x265 Encoder
As an open-source and computationally efficient High Efficiency Video Coding (HEVC) encoder, x265 has been gaining increasing popularity in video applications. x265 provides numerous encoding parameters in view of flexibility. However, proper and efficient setting of parameters often becomes a great challenge in practice. In this paper, we deeply investigate the influence of x265 parameters based on the Slow preset and pick out important parameters in terms of efficiency and complexity. Then a Markov Chain Monte Carlo (MCMC) based algorithm is proposed for efficient parameter adaptation at the target encoding time. This paper shows that carefully selected low-complexity encoding configurations can achieve the coding efficiency comparable to that of high-complexity ones. Specifically, average 26.72% encoding time reduction can be achieved while maintaining similar Rate Distortion (RD) performance to x265 presets using the proposed 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
Ultra-Low Power Wide-Dynamic-Range Universal Interface for Capacitive and Resistive Sensors An Energy-Efficient 13-bit Zero-Crossing ΔΣ Capacitance-to-Digital Converter with 1 pF-to-10 nF Sensing Range Power Optimized Comparator Selecting Method For Stochastic ADC Brain-inspired recurrent neural network with plastic RRAM synapses On the Use of Approximate Multipliers in LMS Adaptive Filters
×
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