{"title":"利用模糊规则去除混合噪声","authors":"A. Taguchi","doi":"10.1109/KES.1998.725843","DOIUrl":null,"url":null,"abstract":"We have proposed fuzzy filters in order to remove additive nonimpulsive noise (e.g., Gaussian noise) while preserving signal details. In this paper, we propose a novel fuzzy filter for removing mixed noise (i.e., Gaussian noise and impulse noise are mixed). In order to remove mixed noise efficiently, we set fuzzy rules by using multiple difference values between arbitrary two pixels in a filter window. We show tuning result of the proposed fuzzy filter and present some simulation results.","PeriodicalId":394492,"journal":{"name":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Removal of mixed noise by using fuzzy rules\",\"authors\":\"A. Taguchi\",\"doi\":\"10.1109/KES.1998.725843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have proposed fuzzy filters in order to remove additive nonimpulsive noise (e.g., Gaussian noise) while preserving signal details. In this paper, we propose a novel fuzzy filter for removing mixed noise (i.e., Gaussian noise and impulse noise are mixed). In order to remove mixed noise efficiently, we set fuzzy rules by using multiple difference values between arbitrary two pixels in a filter window. We show tuning result of the proposed fuzzy filter and present some simulation results.\",\"PeriodicalId\":394492,\"journal\":{\"name\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"volume\":\"131 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KES.1998.725843\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KES.1998.725843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We have proposed fuzzy filters in order to remove additive nonimpulsive noise (e.g., Gaussian noise) while preserving signal details. In this paper, we propose a novel fuzzy filter for removing mixed noise (i.e., Gaussian noise and impulse noise are mixed). In order to remove mixed noise efficiently, we set fuzzy rules by using multiple difference values between arbitrary two pixels in a filter window. We show tuning result of the proposed fuzzy filter and present some simulation results.