Novel Hybrid Conjugate Gradient Technique Based on the Newton Direction Applied to Image Restoration Problem

Authors

  • Romaissa Mellal Laboratory of ACED, Department of Mathematics, 8th May 1945 University, Guelma, Algeria
  • Nabil Sellami Laboratory of ACED, Department of Mathematics, 8th May 1945 University, Guelma, Algeria
  • Basim Abas Hassan College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq

DOI:

https://doi.org/10.19139/soic-2310-5070-2897

Keywords:

Nonlinear Conjugate Gradient, Unconstrained Optimization, Strong Wolfe Line Search, Image Restoration Problems.

Abstract

We introduce a novel hybrid conjugate gradient method for unconstrained optimization, combining the AlBayati-AlAssady and Rivaie-Mustafa-Ismail-Leong approaches, where the convex combination parameter is determined to ensure alignment between the conjugate gradient direction and the Newton direction. Through rigorous theoretical analysis, we establish that the proposed method guarantees sufficient descent properties and achieves global convergence under the strong Wolfe line search conditions.Numerical experiments on image restoration confirm that our method exhibits competitive or superior performance compared to the Fletcher-Reeves algorithm, especially when processing images with higher noise levels.

Author Biographies

Nabil Sellami, Laboratory of ACED, Department of Mathematics, 8th May 1945 University, Guelma, Algeria

Laboratory of ACED, Department of Mathematics.

Basim Abas Hassan, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq

College of Computer Science and Mathematics.

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Published

2025-11-12

How to Cite

Mellal, R., Sellami, N., & Hassan, . B. A. . (2025). Novel Hybrid Conjugate Gradient Technique Based on the Newton Direction Applied to Image Restoration Problem. Statistics, Optimization & Information Computing, 15(3), 1758–1775. https://doi.org/10.19139/soic-2310-5070-2897

Issue

Vol. 15 No. 3 (2026)

Section

Research Articles

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