{"title":"基于联合NLM-Weiner滤波的图像去噪","authors":"C. Shwetha, K. Meenakshy","doi":"10.1109/PICC.2015.7455801","DOIUrl":null,"url":null,"abstract":"This paper presents an image denoising algorithm that uses non local means algorithm together with Weiner filter. The presence of noise halo or rare patch effect in non local means denoised image occurs as a result of large variance between pixel values near the edges. This large variance is reduced by deliberately adding a small amount of blur near the edges before applying non-local means denoising and then filtering by Weiner filter reduces the noise halo effect in the resulting denoised image.","PeriodicalId":373395,"journal":{"name":"2015 International Conference on Power, Instrumentation, Control and Computing (PICC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Combined NLM-Weiner filter based image denoising\",\"authors\":\"C. Shwetha, K. Meenakshy\",\"doi\":\"10.1109/PICC.2015.7455801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an image denoising algorithm that uses non local means algorithm together with Weiner filter. The presence of noise halo or rare patch effect in non local means denoised image occurs as a result of large variance between pixel values near the edges. This large variance is reduced by deliberately adding a small amount of blur near the edges before applying non-local means denoising and then filtering by Weiner filter reduces the noise halo effect in the resulting denoised image.\",\"PeriodicalId\":373395,\"journal\":{\"name\":\"2015 International Conference on Power, Instrumentation, Control and Computing (PICC)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Power, Instrumentation, Control and Computing (PICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PICC.2015.7455801\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Power, Instrumentation, Control and Computing (PICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PICC.2015.7455801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents an image denoising algorithm that uses non local means algorithm together with Weiner filter. The presence of noise halo or rare patch effect in non local means denoised image occurs as a result of large variance between pixel values near the edges. This large variance is reduced by deliberately adding a small amount of blur near the edges before applying non-local means denoising and then filtering by Weiner filter reduces the noise halo effect in the resulting denoised image.