Parameters identification for a nonlinear partial differential equation in image denoising

Q3 Mathematics
A. E. Mourabit
{"title":"Parameters identification for a nonlinear partial differential equation in image denoising","authors":"A. E. Mourabit","doi":"10.2478/mjpaa-2023-0010","DOIUrl":null,"url":null,"abstract":"Abstract In this work and in the context of PDE constrained optimization problems, we are interested in identification of a parameter in the diffusion equation proposed in [1]. We propose to identify this parameter automatically by a gradient descent algorithm to improve the restoration of a noisy image. Finally, we give numerical results to illustrate the performance of the automatic selection of this parameter and compare our numerical results with other image denoising approaches or algorithms.","PeriodicalId":36270,"journal":{"name":"Moroccan Journal of Pure and Applied Analysis","volume":"9 1","pages":"141 - 153"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Moroccan Journal of Pure and Applied Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/mjpaa-2023-0010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract In this work and in the context of PDE constrained optimization problems, we are interested in identification of a parameter in the diffusion equation proposed in [1]. We propose to identify this parameter automatically by a gradient descent algorithm to improve the restoration of a noisy image. Finally, we give numerical results to illustrate the performance of the automatic selection of this parameter and compare our numerical results with other image denoising approaches or algorithms.
图像去噪中非线性偏微分方程的参数辨识
摘要在这项工作中,在PDE约束优化问题的背景下,我们对[1]中提出的扩散方程中的一个参数的识别感兴趣。我们建议通过梯度下降算法自动识别该参数,以提高噪声图像的恢复能力。最后,我们给出了数值结果来说明该参数的自动选择性能,并将我们的数值结果与其他图像去噪方法或算法进行了比较。
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
Moroccan Journal of Pure and Applied Analysis
Moroccan Journal of Pure and Applied Analysis Mathematics-Numerical Analysis
CiteScore
1.60
自引率
0.00%
发文量
27
审稿时长
8 weeks
×
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:481959085
Book学术官方微信