Y. Kondo, Y. Yamaguchi, H. Saito, I. Yoshida, M. Numada, H. Koshimizu
{"title":"用快速m估计方法验证保边降噪滤波器的去噪性能","authors":"Y. Kondo, Y. Yamaguchi, H. Saito, I. Yoshida, M. Numada, H. Koshimizu","doi":"10.1117/12.2592763","DOIUrl":null,"url":null,"abstract":"Random noise injures both the basic image quality and also the following image processing procedures. The low-pass filter is commonly used as the image denoising. Low-pass filter can reduce noise; however, the edge becomes always blur as the side effect. In order to suppress this side effect, we proposed edge preserving noise reduction filter using Fast Mestimation method. As the Proposed method is applied experimentally to the noisy image, it was clarified that the noise was clearly reduced and the performance of edge preserving was realized at the same time. In this study, a quantitative evaluation of the denoising performance of the proposed method is obtained by varying the amount of noise applied and obtaining the denoising ratio.","PeriodicalId":295011,"journal":{"name":"International Conference on Quality Control by Artificial Vision","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Verification of denoising performance of edge-preserving noise reduction filter using fast M-estimation method\",\"authors\":\"Y. Kondo, Y. Yamaguchi, H. Saito, I. Yoshida, M. Numada, H. Koshimizu\",\"doi\":\"10.1117/12.2592763\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Random noise injures both the basic image quality and also the following image processing procedures. The low-pass filter is commonly used as the image denoising. Low-pass filter can reduce noise; however, the edge becomes always blur as the side effect. In order to suppress this side effect, we proposed edge preserving noise reduction filter using Fast Mestimation method. As the Proposed method is applied experimentally to the noisy image, it was clarified that the noise was clearly reduced and the performance of edge preserving was realized at the same time. In this study, a quantitative evaluation of the denoising performance of the proposed method is obtained by varying the amount of noise applied and obtaining the denoising ratio.\",\"PeriodicalId\":295011,\"journal\":{\"name\":\"International Conference on Quality Control by Artificial Vision\",\"volume\":\"127 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Quality Control by Artificial Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2592763\",\"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 Conference on Quality Control by Artificial Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2592763","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Verification of denoising performance of edge-preserving noise reduction filter using fast M-estimation method
Random noise injures both the basic image quality and also the following image processing procedures. The low-pass filter is commonly used as the image denoising. Low-pass filter can reduce noise; however, the edge becomes always blur as the side effect. In order to suppress this side effect, we proposed edge preserving noise reduction filter using Fast Mestimation method. As the Proposed method is applied experimentally to the noisy image, it was clarified that the noise was clearly reduced and the performance of edge preserving was realized at the same time. In this study, a quantitative evaluation of the denoising performance of the proposed method is obtained by varying the amount of noise applied and obtaining the denoising ratio.