{"title":"基于字典学习的高光谱视频压缩感知","authors":"L. Carin","doi":"10.1364/FIO.2012.FM4C.5","DOIUrl":null,"url":null,"abstract":"The proposed approach is capable of efficiently reconstructing large hyperspectral datacubes, including hyperspectral video. Comparisons are made between the proposed algorithm and other techniques employed in compressive sensing, dictionary learning and matrix factorization.","PeriodicalId":91683,"journal":{"name":"Frontiers in optics. Annual Meeting of the Optical Society of America","volume":"32 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2012-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dictionary Learning for Hyperspectral Video Compressive Sensing\",\"authors\":\"L. Carin\",\"doi\":\"10.1364/FIO.2012.FM4C.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed approach is capable of efficiently reconstructing large hyperspectral datacubes, including hyperspectral video. Comparisons are made between the proposed algorithm and other techniques employed in compressive sensing, dictionary learning and matrix factorization.\",\"PeriodicalId\":91683,\"journal\":{\"name\":\"Frontiers in optics. Annual Meeting of the Optical Society of America\",\"volume\":\"32 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in optics. Annual Meeting of the Optical Society of America\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/FIO.2012.FM4C.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in optics. Annual Meeting of the Optical Society of America","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/FIO.2012.FM4C.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dictionary Learning for Hyperspectral Video Compressive Sensing
The proposed approach is capable of efficiently reconstructing large hyperspectral datacubes, including hyperspectral video. Comparisons are made between the proposed algorithm and other techniques employed in compressive sensing, dictionary learning and matrix factorization.