{"title":"编码孔径压缩光谱成像","authors":"Henry Arguello Fuentes, G. Arce","doi":"10.1109/STSIVA.2013.6644909","DOIUrl":null,"url":null,"abstract":"This article overviews the fundamental optical phenomena behind compressive spectral imaging, presents the key mathematical concepts embodying the sensing and reconstruction mechanisms, and describes the optimization framework used to design optimal coded apertures in a number of applications including hyperspectral image reconstruction, spectral selectivity, and super-resolution.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Coded aperture compressive spectral imaging\",\"authors\":\"Henry Arguello Fuentes, G. Arce\",\"doi\":\"10.1109/STSIVA.2013.6644909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article overviews the fundamental optical phenomena behind compressive spectral imaging, presents the key mathematical concepts embodying the sensing and reconstruction mechanisms, and describes the optimization framework used to design optimal coded apertures in a number of applications including hyperspectral image reconstruction, spectral selectivity, and super-resolution.\",\"PeriodicalId\":359994,\"journal\":{\"name\":\"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013\",\"volume\":\"106 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/STSIVA.2013.6644909\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STSIVA.2013.6644909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This article overviews the fundamental optical phenomena behind compressive spectral imaging, presents the key mathematical concepts embodying the sensing and reconstruction mechanisms, and describes the optimization framework used to design optimal coded apertures in a number of applications including hyperspectral image reconstruction, spectral selectivity, and super-resolution.
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