{"title":"H.264视频传输中像素恢复的l1范数最小化","authors":"Ting-Lan Lin, Chang-Yi Fan, Gui-Xiang Huang, Wen-Chih Chen","doi":"10.1109/ISPACS.2012.6473500","DOIUrl":null,"url":null,"abstract":"We consider an application of sparse optimization in the error concealment area. State-of-the-art spatial and temporal error concealment method is improved and compared. By solving for limited numbers of significant predictors using the sparse optimization, our algorithm performs subjectively and objective better for the concealed result.","PeriodicalId":158744,"journal":{"name":"2012 International Symposium on Intelligent Signal Processing and Communications Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"L1-norm minimization in pixel recovery for H.264 video transmission\",\"authors\":\"Ting-Lan Lin, Chang-Yi Fan, Gui-Xiang Huang, Wen-Chih Chen\",\"doi\":\"10.1109/ISPACS.2012.6473500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider an application of sparse optimization in the error concealment area. State-of-the-art spatial and temporal error concealment method is improved and compared. By solving for limited numbers of significant predictors using the sparse optimization, our algorithm performs subjectively and objective better for the concealed result.\",\"PeriodicalId\":158744,\"journal\":{\"name\":\"2012 International Symposium on Intelligent Signal Processing and Communications Systems\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Symposium on Intelligent Signal Processing and Communications Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPACS.2012.6473500\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Symposium on Intelligent Signal Processing and Communications Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPACS.2012.6473500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
L1-norm minimization in pixel recovery for H.264 video transmission
We consider an application of sparse optimization in the error concealment area. State-of-the-art spatial and temporal error concealment method is improved and compared. By solving for limited numbers of significant predictors using the sparse optimization, our algorithm performs subjectively and objective better for the concealed result.