{"title":"扫描电子显微镜图像处理技术","authors":"O. Tutunaru, R. Pascu","doi":"10.1109/SMICND.2019.8924031","DOIUrl":null,"url":null,"abstract":"Quantification of the noise content in the scanning electron microscope image is an important parameter in the signal-to-noise ratio. The most common type of noise in SEM image is the Gaussian noise. We compared different noise reduction filters, like average, median, Gaussian Smoothing and Wiener filters, in order to see the image improvement. Based on the experiment results the most promising is the Wienerfilter.","PeriodicalId":151985,"journal":{"name":"2019 International Semiconductor Conference (CAS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image processing technology for scanning electron microscopy\",\"authors\":\"O. Tutunaru, R. Pascu\",\"doi\":\"10.1109/SMICND.2019.8924031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantification of the noise content in the scanning electron microscope image is an important parameter in the signal-to-noise ratio. The most common type of noise in SEM image is the Gaussian noise. We compared different noise reduction filters, like average, median, Gaussian Smoothing and Wiener filters, in order to see the image improvement. Based on the experiment results the most promising is the Wienerfilter.\",\"PeriodicalId\":151985,\"journal\":{\"name\":\"2019 International Semiconductor Conference (CAS)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Semiconductor Conference (CAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMICND.2019.8924031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Semiconductor Conference (CAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMICND.2019.8924031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image processing technology for scanning electron microscopy
Quantification of the noise content in the scanning electron microscope image is an important parameter in the signal-to-noise ratio. The most common type of noise in SEM image is the Gaussian noise. We compared different noise reduction filters, like average, median, Gaussian Smoothing and Wiener filters, in order to see the image improvement. Based on the experiment results the most promising is the Wienerfilter.