Андрей Насонов, A. Nasonov, Николай Мамаев, N. Mamaev, Ольга Володина, O. Volodina, А. Крылов, A. Krylov
{"title":"Automatic Choice of Denoising Parameter in Perona-Malik Model","authors":"Андрей Насонов, A. Nasonov, Николай Мамаев, N. Mamaev, Ольга Володина, O. Volodina, А. Крылов, A. Krylov","doi":"10.30987/graphicon-2019-2-144-147","DOIUrl":null,"url":null,"abstract":"In this work, we propose a no-reference method for automatic choice of the parameters of Perona-Malik image diffusion algorithm for the problem of image denoising. The idea of the approach it to analyze and quantify the presence of structures in the difference image between the noisy image and the processed image as the mutual information value. We apply the proposed method to photographic images and to retinal images with modeled Gaussian noise with different parameters and analyze the effects of no-reference parameter choice compared to the optimal results. The proposed algorithm shows the effectiveness of no-reference parameter choice for the problem of image denoising.","PeriodicalId":409819,"journal":{"name":"GraphiCon'2019 Proceedings. Volume 2","volume":"17 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GraphiCon'2019 Proceedings. Volume 2","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30987/graphicon-2019-2-144-147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this work, we propose a no-reference method for automatic choice of the parameters of Perona-Malik image diffusion algorithm for the problem of image denoising. The idea of the approach it to analyze and quantify the presence of structures in the difference image between the noisy image and the processed image as the mutual information value. We apply the proposed method to photographic images and to retinal images with modeled Gaussian noise with different parameters and analyze the effects of no-reference parameter choice compared to the optimal results. The proposed algorithm shows the effectiveness of no-reference parameter choice for the problem of image denoising.