{"title":"Multi-mode content-aware motion estimation algorithm for power-aware video coding systems","authors":"Siou-Shen Lin, Po-Chih Tseng, Chia-Ping Lin, Liang-Gee Chen","doi":"10.1109/SIPS.2004.1363056","DOIUrl":null,"url":null,"abstract":"By exploiting the characteristics of the video signal, two content-aware decision criteria are proposed to identify the complexity of motion vectors. Based on these two decision criteria, as well as different combinations of various motion estimation algorithms, four different modes are proposed to allow the computation resources to be varied dynamically between different power constraints. The proposed decision criteria also enable the maximization of quality under each power constraint by a quality-driven diversity-based search approach. According to our simulation results, the proposed algorithm can effectively reduce the computation resources to 40%, 21%, and 3.73% with only 0.0036 dB, 0.01 dB, and 0.16 dB average quality degradation, respectively. As a result, the proposed algorithm is well-suited for video coding systems that desire a power-awareness feature.","PeriodicalId":384858,"journal":{"name":"IEEE Workshop onSignal Processing Systems, 2004. SIPS 2004.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Workshop onSignal Processing Systems, 2004. SIPS 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIPS.2004.1363056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
By exploiting the characteristics of the video signal, two content-aware decision criteria are proposed to identify the complexity of motion vectors. Based on these two decision criteria, as well as different combinations of various motion estimation algorithms, four different modes are proposed to allow the computation resources to be varied dynamically between different power constraints. The proposed decision criteria also enable the maximization of quality under each power constraint by a quality-driven diversity-based search approach. According to our simulation results, the proposed algorithm can effectively reduce the computation resources to 40%, 21%, and 3.73% with only 0.0036 dB, 0.01 dB, and 0.16 dB average quality degradation, respectively. As a result, the proposed algorithm is well-suited for video coding systems that desire a power-awareness feature.