Application of self-organization pso based on region energy in image fusion

This paper presents a wavelet-based image fusion method, in which the self-organizing particle swarm optimization algorithm is applied to image fusion based on region energy. In order to find image fusion by the optimal threshold particles are firsthand formed by thresholds. With comprehensive consideration of the parameters that affect the performance the algorithm, acceleration factors and inertia weights are adaptively adjusted in the self-organizing particle swarm optimization algorithm. Also, to improve the shortcoming of premature convergence of particle swarm optimization, the particles are organized to track the local and global optimal region. The experimental results show that the proposed method can achieve very good fusion performance.