Research and Implementation of Image Correlation Matching Based on Evolutionary Algorithm

Abstract

An improved evolutionary algorithm is proposed, and then it is used to solve image correlation matching. It has some new features: 1) using multi-parent search strategy and stochastic ranking strategy, which can enhance the search ability and exploit the optimum offspring, 2) two mutation strategies are proposed: low probability mutation strategy for the early mutation, and high probability strategy for the late mutation to enhance the diversity of population, the experimental results demonstrate that the performance in this paper outperforms that of other evolutionary algorithms in terms of the quality of the final solution, its stability is better and its computational cost is lower than the cost required by the other techniques compared.