基于H.264帧内编码器结构信息的率失真优化

Babu Hemanth Kumar Aswathappa, K. Rao
{"title":"基于H.264帧内编码器结构信息的率失真优化","authors":"Babu Hemanth Kumar Aswathappa, K. Rao","doi":"10.1109/SSST.2010.5442789","DOIUrl":null,"url":null,"abstract":"In this paper we employ Structural Similarity Index (SSIM) metric in the rate-distortion optimizations of H.264 strictly I-frame encoder to choose the best prediction mode(s). The SSIM is designed to improve on traditional metrics like PSNR and MSE, which have been proved to be inconsistent with human eye perception. The required modifications are done on the JVT reference software JM92 program. The simulation results show that there is reduction in bit rate by 3% while maintaining almost the same video quality and better encoding time","PeriodicalId":6463,"journal":{"name":"2010 42nd Southeastern Symposium on System Theory (SSST)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Rate-distortion optimization using structural information in H.264 strictly Intra-frame encoder\",\"authors\":\"Babu Hemanth Kumar Aswathappa, K. Rao\",\"doi\":\"10.1109/SSST.2010.5442789\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we employ Structural Similarity Index (SSIM) metric in the rate-distortion optimizations of H.264 strictly I-frame encoder to choose the best prediction mode(s). The SSIM is designed to improve on traditional metrics like PSNR and MSE, which have been proved to be inconsistent with human eye perception. The required modifications are done on the JVT reference software JM92 program. The simulation results show that there is reduction in bit rate by 3% while maintaining almost the same video quality and better encoding time\",\"PeriodicalId\":6463,\"journal\":{\"name\":\"2010 42nd Southeastern Symposium on System Theory (SSST)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 42nd Southeastern Symposium on System Theory (SSST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSST.2010.5442789\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 42nd Southeastern Symposium on System Theory (SSST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.2010.5442789","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

本文在H.264严格i帧编码器的率失真优化中,采用结构相似度指标(SSIM)来选择最佳的预测模式。SSIM旨在改进传统的指标,如PSNR和MSE,这些指标已被证明与人眼感知不一致。所需的修改是在JVT参考软件JM92程序上完成的。仿真结果表明,在保持几乎相同的视频质量和较好的编码时间的情况下,比特率降低了3%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rate-distortion optimization using structural information in H.264 strictly Intra-frame encoder
In this paper we employ Structural Similarity Index (SSIM) metric in the rate-distortion optimizations of H.264 strictly I-frame encoder to choose the best prediction mode(s). The SSIM is designed to improve on traditional metrics like PSNR and MSE, which have been proved to be inconsistent with human eye perception. The required modifications are done on the JVT reference software JM92 program. The simulation results show that there is reduction in bit rate by 3% while maintaining almost the same video quality and better encoding time
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