{"title":"通过深度学习的数字全息成像","authors":"Zhenbo Ren, Tianjiao Zeng, E. Lam","doi":"10.1364/COSI.2019.CTU3A.4","DOIUrl":null,"url":null,"abstract":"We propose an end-to-end deep learning method for holographic reconstruction. Through this data-driven approach, it is possible to reconstruct a noise-free image that does not require any prior knowledge.","PeriodicalId":123636,"journal":{"name":"Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Digital holographic imaging via deep learning\",\"authors\":\"Zhenbo Ren, Tianjiao Zeng, E. Lam\",\"doi\":\"10.1364/COSI.2019.CTU3A.4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose an end-to-end deep learning method for holographic reconstruction. Through this data-driven approach, it is possible to reconstruct a noise-free image that does not require any prior knowledge.\",\"PeriodicalId\":123636,\"journal\":{\"name\":\"Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"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.CTU3A.4\",\"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.CTU3A.4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We propose an end-to-end deep learning method for holographic reconstruction. Through this data-driven approach, it is possible to reconstruct a noise-free image that does not require any prior knowledge.
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