Image restoration by multivariate-stochastic optimization using improved particle swarm algorithm

Image restoration is a multivariate-stochastic optimization challenge. In this paper, an improved particle swarm algorithm is proposed for image restoration. The proposed method - Optimal Image Restoration using Improved Particle Swarm Algorithm (OIRIPSA) - is analyzed with an approximated (constrained least square error) and a true cost (mean squared error) measures, respectively. Initial swarm of heuristic solutions is constructed arbitrarily along with problem specific knowledge. An optimistic hyper layer is further integrated to enhance the swarm search procedure by constructing an incipient solution in the neighborhood of the generation's best. OIRIPSA is engendering better restoration than Richardson-Lucy algorithm and a state-of-the-art restoration method.