{"title":"通过深度学习计算全息3D显示器的实时计算机生成全息图","authors":"Sheng-Chi Liu, Jin Li, D. Chu","doi":"10.1364/DH.2019.TU4A.7","DOIUrl":null,"url":null,"abstract":"A deep learning method is proposed to calculate holograms in real-time. After training, it can generate holograms for all R/G/B channels within 10 msec. Simulation results confirm successfully reconstruct the target training and testing images.","PeriodicalId":448778,"journal":{"name":"Digital Holography and Three-Dimensional Imaging 2019","volume":"122 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Calculating Real-time Computer-Generated Holograms for Holographic 3D Displays through Deep Learning\",\"authors\":\"Sheng-Chi Liu, Jin Li, D. Chu\",\"doi\":\"10.1364/DH.2019.TU4A.7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A deep learning method is proposed to calculate holograms in real-time. After training, it can generate holograms for all R/G/B channels within 10 msec. Simulation results confirm successfully reconstruct the target training and testing images.\",\"PeriodicalId\":448778,\"journal\":{\"name\":\"Digital Holography and Three-Dimensional Imaging 2019\",\"volume\":\"122 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digital Holography and Three-Dimensional Imaging 2019\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/DH.2019.TU4A.7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Holography and Three-Dimensional Imaging 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/DH.2019.TU4A.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Calculating Real-time Computer-Generated Holograms for Holographic 3D Displays through Deep Learning
A deep learning method is proposed to calculate holograms in real-time. After training, it can generate holograms for all R/G/B channels within 10 msec. Simulation results confirm successfully reconstruct the target training and testing images.
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