Using High Order Total Variation for Denoising Speckle, Gaussian, Salt & Pepper

S. Ghofrani, H. Markarian
{"title":"Using High Order Total Variation for Denoising Speckle, Gaussian, Salt & Pepper","authors":"S. Ghofrani, H. Markarian","doi":"10.1109/ICMETE.2016.37","DOIUrl":null,"url":null,"abstract":"Noise reduction for image enhancement is the important issue for any image processing algorithm. Total variation (TV) regularization based methods were proposed for multiplicative speckle noise reduction, though sometimes have the undesirable staircase effect. As a solution for this problem, high order TV (High-TV) algorithm was proposed. In this paper we use the High-TV not only for speckle but also Gaussian and salt & pepper noises. The performance among High-TV and some TV based denoising algorithms are also compared in terms of objective and subjective image assessment parameters for two test images and two true SAR images degraded by speckle noise.","PeriodicalId":167368,"journal":{"name":"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMETE.2016.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Noise reduction for image enhancement is the important issue for any image processing algorithm. Total variation (TV) regularization based methods were proposed for multiplicative speckle noise reduction, though sometimes have the undesirable staircase effect. As a solution for this problem, high order TV (High-TV) algorithm was proposed. In this paper we use the High-TV not only for speckle but also Gaussian and salt & pepper noises. The performance among High-TV and some TV based denoising algorithms are also compared in terms of objective and subjective image assessment parameters for two test images and two true SAR images degraded by speckle noise.
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
用高阶总变分去噪斑点,高斯,盐和胡椒
图像增强的降噪是任何图像处理算法的重要问题。提出了基于总变分(TV)正则化的乘性散斑噪声降噪方法,但有时会产生不良的阶梯效应。为了解决这一问题,提出了高阶电视(high -TV)算法。在本文中,我们不仅对散斑噪声,而且对高斯噪声和椒盐噪声也使用了High-TV。针对两幅测试图像和两幅被散斑噪声破坏的真实SAR图像,比较了High-TV和一些基于TV的去噪算法的客观和主观图像评价参数。
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
Study of E-shaped Patch Antenna with Two Rectangular Slots Text Summarization of Hindi Documents Using Rule Based Approach Estimation of Respiratory Rate from the ECG Using Instantaneous Frequency Tracking FxLMS Algorithm Low Power and High Performance Ring Counter Using Pulsed Latch Technique Satellite Image Enhancement using Discrete Wavelet Transform, Singular Value Decomposition and its Noise Performance Analysis
×
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