Loading [MathJax]/jax/output/CommonHTML/config.js
Computer Research and Modeling
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Computer Research and Modeling:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Computer Research and Modeling, 2024, Volume 16, Issue 4, Pages 841–853
DOI: https://doi.org/10.20537/2076-7633-2024-16-4-841-853
(Mi crm1194)
 

NUMERICAL METHODS AND THE BASIS FOR THEIR APPLICATION

Noise removal from images using the proposed three-term conjugate gradient algorithm

H. M. Khudhura, I. H. Halilb

a Mathematics Department, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq
b Department of Mathematics, College of Science, University of Kirkuk, Kirkuk, Iraq
References:
Abstract: Conjugate gradient algorithms represent an important class of unconstrained optimization algorithms with strong local and global convergence properties and simple memory requirements. These algorithms have advantages that place them between the steep regression method and Newton’s algorithm because they require calculating the first derivatives only and do not require calculating and storing the second derivatives that Newton’s algorithm needs. They are also faster than the steep descent algorithm, meaning that they have overcome the slow convergence of this algorithm, and it does not need to calculate the Hessian matrix or any of its approximations, so it is widely used in optimization applications. This study proposes a novel method for image restoration by fusing the convex combination method with the hybrid (CG) method to create a hybrid three-term (CG) algorithm. Combining the features of both the Fletcher and Revees (FR) conjugate parameter and the hybrid Fletcher and Revees (FR), we get the search direction conjugate parameter. The search direction is the result of concatenating the gradient direction, the previous search direction, and the gradient from the previous iteration. We have shown that the new algorithm possesses the properties of global convergence and descent when using an inexact search line, relying on the standard Wolfe conditions, and using some assumptions. To guarantee the effectiveness of the suggested algorithm and processing image restoration problems. The numerical results of the new algorithm show high efficiency and accuracy in image restoration and speed of convergence when used in image restoration problems compared to Fletcher and Revees (FR) and three-term Fletcher and Revees (TTFR).
Keywords: nonsmooth, restoration, globally, descent, numerical, optimization
Received: 10.09.2023
Revised: 14.05.2024
Accepted: 16.07.2024
Document Type: Article
UDC: 51
Language: English
Citation: H. M. Khudhur, I. H. Halil, “Noise removal from images using the proposed three-term conjugate gradient algorithm”, Computer Research and Modeling, 16:4 (2024), 841–853
Citation in format AMSBIB
\Bibitem{KhuHal24}
\by H.~M.~Khudhur, I.~H.~Halil
\paper Noise removal from images using the proposed three-term conjugate gradient algorithm
\jour Computer Research and Modeling
\yr 2024
\vol 16
\issue 4
\pages 841--853
\mathnet{http://mi.mathnet.ru/crm1194}
\crossref{https://doi.org/10.20537/2076-7633-2024-16-4-841-853}
Linking options:
  • https://www.mathnet.ru/eng/crm1194
  • https://www.mathnet.ru/eng/crm/v16/i4/p841
  • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Research and Modeling
    Statistics & downloads:
    Abstract page:48
    Full-text PDF :26
    References:18
     
      Contact us:
    math-net2025_01@mi-ras.ru
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2025