{"title":"基于b样条的扫描电镜图像信噪比估计技术","authors":"Z. X. Yeap, K. Sim, C. Tso","doi":"10.1109/ICORAS.2016.7872617","DOIUrl":null,"url":null,"abstract":"A new signal-to-noise ratio (SNR) estimation technique is proposed for the scanning electron microscope image. Based on only a single image, an estimation technique named B-spline is proposed. Three existing techniques are applied to compare with the performance of the proposed method in terms of the zero-offset point, SNR and percentage error. They are the nearest neighborhood, first order interpolation, and a combination of these two methods. A t-test is conducted on the proposed method. Noise variance is estimated from the SNR calculated and a Wiener filter will be used to filter the noise with the filtered images being similar to noise-free images.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Signal-to-noise ratio estimation technique for SEM image using B-spline\",\"authors\":\"Z. X. Yeap, K. Sim, C. Tso\",\"doi\":\"10.1109/ICORAS.2016.7872617\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new signal-to-noise ratio (SNR) estimation technique is proposed for the scanning electron microscope image. Based on only a single image, an estimation technique named B-spline is proposed. Three existing techniques are applied to compare with the performance of the proposed method in terms of the zero-offset point, SNR and percentage error. They are the nearest neighborhood, first order interpolation, and a combination of these two methods. A t-test is conducted on the proposed method. Noise variance is estimated from the SNR calculated and a Wiener filter will be used to filter the noise with the filtered images being similar to noise-free images.\",\"PeriodicalId\":393534,\"journal\":{\"name\":\"2016 International Conference on Robotics, Automation and Sciences (ICORAS)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Robotics, Automation and Sciences (ICORAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICORAS.2016.7872617\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORAS.2016.7872617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Signal-to-noise ratio estimation technique for SEM image using B-spline
A new signal-to-noise ratio (SNR) estimation technique is proposed for the scanning electron microscope image. Based on only a single image, an estimation technique named B-spline is proposed. Three existing techniques are applied to compare with the performance of the proposed method in terms of the zero-offset point, SNR and percentage error. They are the nearest neighborhood, first order interpolation, and a combination of these two methods. A t-test is conducted on the proposed method. Noise variance is estimated from the SNR calculated and a Wiener filter will be used to filter the noise with the filtered images being similar to noise-free images.