{"title":"一种新的基于patch的噪声滤波方法","authors":"Q. B. Do, Azeddine Beghdadi, M. Luong","doi":"10.1109/WOSSPA.2011.5931499","DOIUrl":null,"url":null,"abstract":"A common framework is proposed for Gaussian, unilateral, bilateral and non-local means filters. A new denoising method is then introduced for removing additive independent Gaussian noise. It is adapted and applied for filtering signal-dependent noise such as film grain noise. The main idea is to transform the signal-dependent into independent additive Gaussian noise using a nonlinear transformation prior to filtering. The obtained results clearly demonstrate the efficiency of the proposed method.","PeriodicalId":343415,"journal":{"name":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new patch-based approach for noise filetring\",\"authors\":\"Q. B. Do, Azeddine Beghdadi, M. Luong\",\"doi\":\"10.1109/WOSSPA.2011.5931499\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A common framework is proposed for Gaussian, unilateral, bilateral and non-local means filters. A new denoising method is then introduced for removing additive independent Gaussian noise. It is adapted and applied for filtering signal-dependent noise such as film grain noise. The main idea is to transform the signal-dependent into independent additive Gaussian noise using a nonlinear transformation prior to filtering. The obtained results clearly demonstrate the efficiency of the proposed method.\",\"PeriodicalId\":343415,\"journal\":{\"name\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOSSPA.2011.5931499\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2011.5931499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A common framework is proposed for Gaussian, unilateral, bilateral and non-local means filters. A new denoising method is then introduced for removing additive independent Gaussian noise. It is adapted and applied for filtering signal-dependent noise such as film grain noise. The main idea is to transform the signal-dependent into independent additive Gaussian noise using a nonlinear transformation prior to filtering. The obtained results clearly demonstrate the efficiency of the proposed method.