A survey on image restoration using hybrid channel based on firefly algorithm

B. B. Csam, F. G. Tharika, K. I. Luxci, N. Kumar
{"title":"A survey on image restoration using hybrid channel based on firefly algorithm","authors":"B. B. Csam, F. G. Tharika, K. I. Luxci, N. Kumar","doi":"10.1109/ICICES.2017.8070727","DOIUrl":null,"url":null,"abstract":"In the diagnostic medical images, the critical component is to lessen the Gaussian noise, which is found in the medical images and make better picture quality. In many cases, the speckle noise corrupts the fine subtle elements and edge definitions of the images. so it ought to be filtered. In this paper, a computed aided diagnostic system for finding the amiable and threatening liver tumours from computed tomography images is presented. This paper proposes the distinctive hybrid techniques for evacuation of mixed type of noise from the images and the image restoration is achieved by the firefly algorithm. Noise arise due to different variables like bit error rate, malfunctioning of camera sensor cells, dead pixels etc. The Hybrid filter can expel mixed type of noise. The quality of the enhanced image is measured by means of the Root mean square error(RMSE), Peak signal to noise ratio(PSNR).","PeriodicalId":134931,"journal":{"name":"2017 International Conference on Information Communication and Embedded Systems (ICICES)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Information Communication and Embedded Systems (ICICES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICES.2017.8070727","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

In the diagnostic medical images, the critical component is to lessen the Gaussian noise, which is found in the medical images and make better picture quality. In many cases, the speckle noise corrupts the fine subtle elements and edge definitions of the images. so it ought to be filtered. In this paper, a computed aided diagnostic system for finding the amiable and threatening liver tumours from computed tomography images is presented. This paper proposes the distinctive hybrid techniques for evacuation of mixed type of noise from the images and the image restoration is achieved by the firefly algorithm. Noise arise due to different variables like bit error rate, malfunctioning of camera sensor cells, dead pixels etc. The Hybrid filter can expel mixed type of noise. The quality of the enhanced image is measured by means of the Root mean square error(RMSE), Peak signal to noise ratio(PSNR).
基于萤火虫算法的混合信道图像恢复研究
在医学诊断图像中,降低医学图像中存在的高斯噪声,提高图像质量是关键。在许多情况下,散斑噪声会破坏图像的精细元素和边缘定义。所以它应该被过滤。本文介绍了一种计算机辅助诊断系统,用于从计算机断层图像中发现良性和威胁性肝脏肿瘤。本文提出了一种独特的混合技术,用于从图像中去除混合类型的噪声,并通过萤火虫算法实现图像的恢复。噪声是由不同的变量引起的,如误码率、相机传感器单元的故障、死像素等。混合滤波器可以排除混合型噪声。用均方根误差(RMSE)、峰值信噪比(PSNR)来衡量增强后图像的质量。
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 求助全文
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