{"title":"中子图像去噪的改进PM方法","authors":"Han Ye, S. Qiao, Chenyi Zhao","doi":"10.1109/CISP-BMEI48845.2019.8965744","DOIUrl":null,"url":null,"abstract":"Due to the influence of many physical factors of the neutron imaging system, the resulting neutron images usually suffer from severe noise pollution. Traditional PM-based methods cannot balance the noise removing and details preserving for neutron images. To address this problem, an improved partial differential equation method for neutron image denoising is proposed, in which the anisotropic diffusion properties are considered. The experimental results show that compared with the traditional PM and PM-based methods, the proposed method can effectively remove the Gaussian noise and achieve satisfying visual effect.","PeriodicalId":257666,"journal":{"name":"2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Improved PM Method for Neutron Image Denoising\",\"authors\":\"Han Ye, S. Qiao, Chenyi Zhao\",\"doi\":\"10.1109/CISP-BMEI48845.2019.8965744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the influence of many physical factors of the neutron imaging system, the resulting neutron images usually suffer from severe noise pollution. Traditional PM-based methods cannot balance the noise removing and details preserving for neutron images. To address this problem, an improved partial differential equation method for neutron image denoising is proposed, in which the anisotropic diffusion properties are considered. The experimental results show that compared with the traditional PM and PM-based methods, the proposed method can effectively remove the Gaussian noise and achieve satisfying visual effect.\",\"PeriodicalId\":257666,\"journal\":{\"name\":\"2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP-BMEI48845.2019.8965744\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI48845.2019.8965744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Due to the influence of many physical factors of the neutron imaging system, the resulting neutron images usually suffer from severe noise pollution. Traditional PM-based methods cannot balance the noise removing and details preserving for neutron images. To address this problem, an improved partial differential equation method for neutron image denoising is proposed, in which the anisotropic diffusion properties are considered. The experimental results show that compared with the traditional PM and PM-based methods, the proposed method can effectively remove the Gaussian noise and achieve satisfying visual effect.