{"title":"块匹配运动估计算法分析","authors":"P. Muralidhar, C. Rao","doi":"10.1109/ICCCNT.2013.6726718","DOIUrl":null,"url":null,"abstract":"Motion estimation is one of the most important tasks in the current standards of video compression. In this paper seven different block matching motion estimation algorithms are analysed for fast motion estimation in video coding. The simulation results of the algorithms are compared based on PSNR, average time taken per frame, total number of search points per macro block and time taken per macro block.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Analysis of block matching motion estimation algorithms\",\"authors\":\"P. Muralidhar, C. Rao\",\"doi\":\"10.1109/ICCCNT.2013.6726718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Motion estimation is one of the most important tasks in the current standards of video compression. In this paper seven different block matching motion estimation algorithms are analysed for fast motion estimation in video coding. The simulation results of the algorithms are compared based on PSNR, average time taken per frame, total number of search points per macro block and time taken per macro block.\",\"PeriodicalId\":6330,\"journal\":{\"name\":\"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCNT.2013.6726718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2013.6726718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of block matching motion estimation algorithms
Motion estimation is one of the most important tasks in the current standards of video compression. In this paper seven different block matching motion estimation algorithms are analysed for fast motion estimation in video coding. The simulation results of the algorithms are compared based on PSNR, average time taken per frame, total number of search points per macro block and time taken per macro block.
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