Applied PSO-RBF to Aerial and Satellite Remote Sensing Image Texture Classification

Particle swarm optimization(PSO) is a new evolutionary computing technique which is based on swarm intelligence.Kernel function parameter selection problem is transformed into the optimization problem and PSO is used to get the optimal kernel function parameters.The combined algorithm of PSO and RBF(PSO-RBF) is applied to aerial and satellite remote sensing image texture classification.The experimental results show that the proposed method is effective.