Speckle Noise Reduction from Medical Images Using Gaussian Fuzzy Membership Function

P. Biswas, K. K. Halder
{"title":"Speckle Noise Reduction from Medical Images Using Gaussian Fuzzy Membership Function","authors":"P. Biswas, K. K. Halder","doi":"10.1109/ICEEE54059.2021.9718944","DOIUrl":null,"url":null,"abstract":"The primary concept of this paper is a fuzzy membership function-based filter with the expertise to reduce speckle noise that is often utilized in clinical diagnosis such as ultrasonography. In medical science, image sharpening is a highly effective approach for recognizing human inner organs and body tissues. Speckle noise is multiplicative in nature and it highly affects the image and reduces some useful information. The target of image noise reduction is to extract the genuine image from a noisy speckled image. In this paper, a Gaussian fuzzy-based system has been developed that is fast and provides good accuracy depending upon the membership function. Also, experimental results demonstrate that the proposed algorithm ensures better filtering quality and image restoration ability in comparison with others.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE54059.2021.9718944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The primary concept of this paper is a fuzzy membership function-based filter with the expertise to reduce speckle noise that is often utilized in clinical diagnosis such as ultrasonography. In medical science, image sharpening is a highly effective approach for recognizing human inner organs and body tissues. Speckle noise is multiplicative in nature and it highly affects the image and reduces some useful information. The target of image noise reduction is to extract the genuine image from a noisy speckled image. In this paper, a Gaussian fuzzy-based system has been developed that is fast and provides good accuracy depending upon the membership function. Also, experimental results demonstrate that the proposed algorithm ensures better filtering quality and image restoration ability in comparison with others.
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
基于高斯模糊隶属函数的医学图像斑点降噪
本文的主要概念是基于模糊隶属函数的滤波器,该滤波器具有降低斑点噪声的专业知识,斑点噪声通常用于临床诊断,如超声检查。在医学上,图像锐化是识别人体内部器官和身体组织的一种非常有效的方法。散斑噪声本质上是乘性的,它对图像的影响很大,减少了一些有用的信息。图像降噪的目标是从带有噪声的斑点图像中提取真实图像。本文开发了一种基于高斯模糊的系统,该系统不仅速度快,而且依赖于隶属函数提供了良好的精度。实验结果表明,该算法具有较好的滤波质量和图像恢复能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Computer-Aided Polyp Removal Detection in Endoscopic Images FPGA based Histogram Equalization for Image Processing Spreading Loss Model for Channel Characterization of Future 6G Terahertz Communication Networks Impact of Cladding Rectangular Bars on the Antiresonant Hollow Core Fiber Predicting Autism Spectrum Disorder Based On Gender Using Machine Learning Techniques
×
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