Particle Swarm Optimization for Reconstruction of Penumbral Images

Abstract

Penumbral imaging is a power imaging technique for radiations with long mean-free path. Since the reconstruction is based on deconvolution, the technique is sensitive to noise contained in penumbral images. The reconstruction of penumbral images can be viewed as an optimization problem by optimizing its cost function. Though conventional local optimization techniques, such as the gradient decent method, can be used for penumbral image reconstructions, these methods need good initial values for estimation in order to avoid the local minimum. In this paper, we propose a new approach using particle swarm optimization (PSO) for penumbral image reconstructions. Particle swarm optimization is a newly proposed stochastic, population-based evolutionary global optimization algorithm. The effectiveness of PSO has been demonstrated.