基于模型的超声图像斑点噪声去除技术

M. Mohammadi, R. Mokhtari
{"title":"基于模型的超声图像斑点噪声去除技术","authors":"M. Mohammadi, R. Mokhtari","doi":"10.1109/CSICC52343.2021.9420572","DOIUrl":null,"url":null,"abstract":"This paper proposes an equation based on a nonlinear filter for speckle noise removal by introducing a region indicator. The use of Gaussian convolution in the proposed region indicator makes the quality of the edges of the image better than other models. The proposed equation also removes noise well due to having a nonlinear filter while preserving important image details such as edges. Experimental results show that the proposed model can handle speckle noise removal quite well.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"36 10","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Model-Based on Filtration Technique for Speckle Noise Removal from Ultrasound Images\",\"authors\":\"M. Mohammadi, R. Mokhtari\",\"doi\":\"10.1109/CSICC52343.2021.9420572\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an equation based on a nonlinear filter for speckle noise removal by introducing a region indicator. The use of Gaussian convolution in the proposed region indicator makes the quality of the edges of the image better than other models. The proposed equation also removes noise well due to having a nonlinear filter while preserving important image details such as edges. Experimental results show that the proposed model can handle speckle noise removal quite well.\",\"PeriodicalId\":374593,\"journal\":{\"name\":\"2021 26th International Computer Conference, Computer Society of Iran (CSICC)\",\"volume\":\"36 10\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 26th International Computer Conference, Computer Society of Iran (CSICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSICC52343.2021.9420572\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSICC52343.2021.9420572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文通过引入区域指示器,提出了一种基于非线性滤波的散斑噪声去除方程。在提出的区域指示器中使用高斯卷积使得图像的边缘质量优于其他模型。由于具有非线性滤波器,所提出的方程还可以很好地去除噪声,同时保留重要的图像细节,如边缘。实验结果表明,该模型能较好地去除散斑噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Model-Based on Filtration Technique for Speckle Noise Removal from Ultrasound Images
This paper proposes an equation based on a nonlinear filter for speckle noise removal by introducing a region indicator. The use of Gaussian convolution in the proposed region indicator makes the quality of the edges of the image better than other models. The proposed equation also removes noise well due to having a nonlinear filter while preserving important image details such as edges. Experimental results show that the proposed model can handle speckle noise removal quite well.
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
期刊最新文献
Transfer Learning for End-to-End ASR to Deal with Low-Resource Problem in Persian Language An SDN-based Firewall for Networks with Varying Security Requirements A Face-Mask Detection Approach based on YOLO Applied for a New Collected Dataset Telegram group recommendation based on users' migration Design of an IoT-based Flood Early Detection System using Machine Learning
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1