{"title":"孔径滤波器的实现噪声去除","authors":"J. Chlapinski, S. Marshall","doi":"10.1109/MIXDES.2006.1706661","DOIUrl":null,"url":null,"abstract":"This paper describes implementation for noise removal based on aperture operators. Aperture operators are a subclass of window operators used in automatic filter design. In this implementation, a typical improvement of 30-50% was observed with respect to MSE as compared to well-known median and adaptive Wiener filtering methods","PeriodicalId":318768,"journal":{"name":"Proceedings of the International Conference Mixed Design of Integrated Circuits and System, 2006. MIXDES 2006.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Aperture Filters Implementation For Noise Removal\",\"authors\":\"J. Chlapinski, S. Marshall\",\"doi\":\"10.1109/MIXDES.2006.1706661\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes implementation for noise removal based on aperture operators. Aperture operators are a subclass of window operators used in automatic filter design. In this implementation, a typical improvement of 30-50% was observed with respect to MSE as compared to well-known median and adaptive Wiener filtering methods\",\"PeriodicalId\":318768,\"journal\":{\"name\":\"Proceedings of the International Conference Mixed Design of Integrated Circuits and System, 2006. MIXDES 2006.\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference Mixed Design of Integrated Circuits and System, 2006. MIXDES 2006.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MIXDES.2006.1706661\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference Mixed Design of Integrated Circuits and System, 2006. MIXDES 2006.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIXDES.2006.1706661","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes implementation for noise removal based on aperture operators. Aperture operators are a subclass of window operators used in automatic filter design. In this implementation, a typical improvement of 30-50% was observed with respect to MSE as compared to well-known median and adaptive Wiener filtering methods