{"title":"Fractional Anisotropic Diffusion For Image Denoising","authors":"S. K. Chandra, Manish Kumar Bajpai","doi":"10.1109/IADCC.2018.8692094","DOIUrl":null,"url":null,"abstract":"An image denoising plays an important role in wide variety of applications. It is one of critical operation in image processing. Image denoising without losing important features is very difficult and challenging task. Many of the techniques have been proposed for image denoising. But, most of the techniques fail to preserve fine details in the image. In this work, a fractional anisotropic model is being presented which not only removes noise but also preserve fine details present in the image. Qualitative and quantitative analysis has been performed. It has been found that the proposed method is superior in image de-noising.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 8th International Advance Computing Conference (IACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IADCC.2018.8692094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
An image denoising plays an important role in wide variety of applications. It is one of critical operation in image processing. Image denoising without losing important features is very difficult and challenging task. Many of the techniques have been proposed for image denoising. But, most of the techniques fail to preserve fine details in the image. In this work, a fractional anisotropic model is being presented which not only removes noise but also preserve fine details present in the image. Qualitative and quantitative analysis has been performed. It has been found that the proposed method is superior in image de-noising.