{"title":"New fast motion estimation algorithm in video coding","authors":"A. V. Paramkusam, V. Reddy","doi":"10.1109/RAICS.2011.6069351","DOIUrl":null,"url":null,"abstract":"The new fast full search motion estimation algorithm for optimal motion estimation is proposed in this paper. The computational process of boundaries and possibility of early rejection of non best candidate blocks in Successive Elimination Algorithm (SEA), Multilevel Successive Elimination Algorithm (MSEA) and Fine Granularity Successive Elimination (FGSE) are theoretically and practically analyzed. Based on these analyzes, we present two methods. The first method is Fast Computing Method (FCM) which takes advantage of mathematical indications of redundancy to reduce the number of operations required to compute the boundaries. The second method is Best Initial Matching Error Predictive Method (BIMEPM) which predicts the best initial matching error. With these methods, the operation number for proposed motion estimation is reduced down to 1/52 of Full Search (FS). But MSEA and FGSE algorithms can reduce computations by 1/40 and 1/42 of FS.","PeriodicalId":394515,"journal":{"name":"2011 IEEE Recent Advances in Intelligent Computational Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Recent Advances in Intelligent Computational Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAICS.2011.6069351","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The new fast full search motion estimation algorithm for optimal motion estimation is proposed in this paper. The computational process of boundaries and possibility of early rejection of non best candidate blocks in Successive Elimination Algorithm (SEA), Multilevel Successive Elimination Algorithm (MSEA) and Fine Granularity Successive Elimination (FGSE) are theoretically and practically analyzed. Based on these analyzes, we present two methods. The first method is Fast Computing Method (FCM) which takes advantage of mathematical indications of redundancy to reduce the number of operations required to compute the boundaries. The second method is Best Initial Matching Error Predictive Method (BIMEPM) which predicts the best initial matching error. With these methods, the operation number for proposed motion estimation is reduced down to 1/52 of Full Search (FS). But MSEA and FGSE algorithms can reduce computations by 1/40 and 1/42 of FS.