{"title":"纹理替换编码的并行框架","authors":"J. Wan, Jinbao Song, Long Ye, Qin Zhang","doi":"10.1109/ICEIT.2010.5607785","DOIUrl":null,"url":null,"abstract":"Image can be parsed into two main categories of representation: structure contour and region texture. However, real-time application of TSC is limited due to its inherent complexity and computational intensity. In this paper, we proposed a distributed parallel TSC framework based on MPI. This framework is implemented on a dedicated cluster. Experiments have demonstrated that our parallel framework can improve the TSC efficiency significantly and achieve optimal restoration.","PeriodicalId":346498,"journal":{"name":"2010 International Conference on Educational and Information Technology","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A parallel framework for texture substitution coding\",\"authors\":\"J. Wan, Jinbao Song, Long Ye, Qin Zhang\",\"doi\":\"10.1109/ICEIT.2010.5607785\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image can be parsed into two main categories of representation: structure contour and region texture. However, real-time application of TSC is limited due to its inherent complexity and computational intensity. In this paper, we proposed a distributed parallel TSC framework based on MPI. This framework is implemented on a dedicated cluster. Experiments have demonstrated that our parallel framework can improve the TSC efficiency significantly and achieve optimal restoration.\",\"PeriodicalId\":346498,\"journal\":{\"name\":\"2010 International Conference on Educational and Information Technology\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Educational and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEIT.2010.5607785\",\"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 International Conference on Educational and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEIT.2010.5607785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A parallel framework for texture substitution coding
Image can be parsed into two main categories of representation: structure contour and region texture. However, real-time application of TSC is limited due to its inherent complexity and computational intensity. In this paper, we proposed a distributed parallel TSC framework based on MPI. This framework is implemented on a dedicated cluster. Experiments have demonstrated that our parallel framework can improve the TSC efficiency significantly and achieve optimal restoration.
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