中子图像去噪的改进PM方法

Han Ye, S. Qiao, Chenyi Zhao
{"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}
引用次数: 2

摘要

由于中子成像系统中许多物理因素的影响,生成的中子图像通常会受到严重的噪声污染。传统的基于pm的方法无法平衡中子图像的去噪和细节保留。针对这一问题,提出了一种考虑中子图像各向异性扩散特性的改进偏微分方程去噪方法。实验结果表明,与传统的PM和基于PM的方法相比,该方法可以有效地去除高斯噪声,达到满意的视觉效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved PM Method for Neutron Image Denoising
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信