Efficient New Conjugate Gradient Methods for Removing Impulse Noise Images

Authors

  • Basim A. Hassan Department of Mathematics, College of Computers Sciences and Mathematics, University of Mosul, Mosul, Iraq. Email:
  • Hameed Sadiq

DOI:

https://doi.org/10.29020/nybg.ejpam.v15i4.4568

Keywords:

Optimization, impulse noise, Conjugate gradient method, Global convergence

Abstract

In most applications, denoising image is fundamental to subsequent image processing operations. In this research, we derivation a new formula of conjugate gradient methods based on the quadratic model. The fact that the search direction created at each iteration of the proposed approach is descending and independent of the line search makes it interesting. The use of Wolfe
conditions also determines the global convergence of the suggested approach. To prove the viability of the suggested approach, comparison tests on impulse noise reduction are given.

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Published

2022-10-31

How to Cite

Hassan, B. A., & Sadiq, H. (2022). Efficient New Conjugate Gradient Methods for Removing Impulse Noise Images. European Journal of Pure and Applied Mathematics, 15(4), 2011–2021. https://doi.org/10.29020/nybg.ejpam.v15i4.4568

Issue

Vol. 15 No. 4: (October 2022)

Section

Nonlinear Analysis

License

Copyright (c) 2022 European Journal of Pure and Applied Mathematics

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