Image restoration using an inertial viscosity fixed point algorithm

TL;DR

This paper introduces a new inertial viscosity fixed point algorithm for image restoration that improves image quality by effectively handling degenerate images, with proven convergence and better performance than existing methods.

Contribution

The paper proposes a novel inertial viscosity fixed point algorithm for image restoration, demonstrating improved results and convergence in Hilbert spaces compared to prior algorithms.

Findings

The algorithm achieves higher quality image restoration.

Inertial and viscosity effects enhance algorithm performance.

The method outperforms some existing algorithms in tests.

Abstract

The image restoration problem is one of the popular topics in image processing studied by many authors on account of its applications in various areas. The aim of this paper is to present a new algorithm by using viscosity approximation with inertial effect for finding a common fixed point of an infinite family of nonexpansive mappings in a Hilbert space and obtaining more quality images from degenerate images. Some strong convergence theorems are proved under mild conditions. The obtained results are applied to solve monotone inclusion problems, convex minimization problems, variational inequality problems and generalized equilibrium problems. It is shown that the proposed algorithm performs better than some other algorithms. Also, the effects of inertial and viscosity terms in the algorithm on image restoration have been investigated.