Denoising an image based on particle swarm optimization (PSO)‎ algorithm

Abstract EN

This work aims to provide processing on noised image based on the particle swarm optimization (PSO) method using a formal analogy with physical systems.

By postulating that the swarm motion behaves similar to both classical and quantum particles, The proposed system have been established a direct connection between separate fields of study,.

Within this framework, it becomes quite can to employ the recently introduced quantum PSO algorithm to demised image.

The physical theory of the PSO (particle swarm optimization) is used to suggest some improvements in the algorithm itself.

At the end, we provide a panorama of applications demonstrating the power of the PSO, classical and quantum, in handling difficult engineering problems.

The goal of this work is to provide a general multi-disciplinary view on various topics in image processing, with unified framework of the swarm dynamics.

At the end, the proposed PSO algorithm is used to optimize the best degree for de-noising.

Simulation results show that the excessive smoothness of proposed method of conventional methods are used for image processing.