{"title":"基于多尺度Hadamard模式的自适应压缩感知","authors":"V. Kravets, A. Stern","doi":"10.1364/COSI.2019.JW2A.21","DOIUrl":null,"url":null,"abstract":"We introduce an efficient adaptive compressive sensing technique that utilizes the zero-trees concept. The method uses multiscale ordered Hadamard sampling and its relation to the Haar wavelet, therefore is particularly useful for single pixel imaging.","PeriodicalId":123636,"journal":{"name":"Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Compressive Sensing with Multiscale Hadamard Patterns\",\"authors\":\"V. Kravets, A. Stern\",\"doi\":\"10.1364/COSI.2019.JW2A.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce an efficient adaptive compressive sensing technique that utilizes the zero-trees concept. The method uses multiscale ordered Hadamard sampling and its relation to the Haar wavelet, therefore is particularly useful for single pixel imaging.\",\"PeriodicalId\":123636,\"journal\":{\"name\":\"Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP)\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/COSI.2019.JW2A.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/COSI.2019.JW2A.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Compressive Sensing with Multiscale Hadamard Patterns
We introduce an efficient adaptive compressive sensing technique that utilizes the zero-trees concept. The method uses multiscale ordered Hadamard sampling and its relation to the Haar wavelet, therefore is particularly useful for single pixel imaging.
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