{"title":"人工神经网络方法在数字全息重建图像增强中的应用","authors":"Gülhan Ustabas Kaya, Z. Saraç","doi":"10.7212/ZKUFBD.V8I2.1186","DOIUrl":null,"url":null,"abstract":"The aim of paper is to use an artificial neural network approach for enhancement of three dimensional image reconstructed in digital holography. An artificial neural network method based on Gerchberg-Saxton algorithm is implemented to reduce the noise and increase the brightness of this image. The results of proposed method have been presented by a relative error. In addition, these relative error figures are supported with error histogram obtained from MATLAB neural network fitting toolbox.","PeriodicalId":17742,"journal":{"name":"Karaelmas Science and Engineering Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Usage of artificial neural networks method for image enhancement of reconstructed image in digital holography\",\"authors\":\"Gülhan Ustabas Kaya, Z. Saraç\",\"doi\":\"10.7212/ZKUFBD.V8I2.1186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of paper is to use an artificial neural network approach for enhancement of three dimensional image reconstructed in digital holography. An artificial neural network method based on Gerchberg-Saxton algorithm is implemented to reduce the noise and increase the brightness of this image. The results of proposed method have been presented by a relative error. In addition, these relative error figures are supported with error histogram obtained from MATLAB neural network fitting toolbox.\",\"PeriodicalId\":17742,\"journal\":{\"name\":\"Karaelmas Science and Engineering Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Karaelmas Science and Engineering Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7212/ZKUFBD.V8I2.1186\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Karaelmas Science and Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7212/ZKUFBD.V8I2.1186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Usage of artificial neural networks method for image enhancement of reconstructed image in digital holography
The aim of paper is to use an artificial neural network approach for enhancement of three dimensional image reconstructed in digital holography. An artificial neural network method based on Gerchberg-Saxton algorithm is implemented to reduce the noise and increase the brightness of this image. The results of proposed method have been presented by a relative error. In addition, these relative error figures are supported with error histogram obtained from MATLAB neural network fitting toolbox.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
