Abstract: This thesis describes the problem of image matching first，then it introduces the standard version of PSO（Particle Swarm Optimization） algorithm and some relative conceptions，at last，it demonstrates how to use PSO algorithm to solve the image match problem.The result of experiment shows that the image match algorithm based on PSO overcomes the disadvantages of common algorithms on condition of keeping the precision，which are a large amount of operations and costing long time，and the method can match the requests of the precision and the speed in real application situation.

摘要： 首先对图像匹配问题进行了描述，接着简单介绍了标准粒子群优化算法及其一些基本概念。最后，引出如何运用粒子群优化算法来求解图像匹配问题。对实验结果的分析表明：基于粒子群优化算法的图像匹配算法能够在不失匹配精度的条件下，克服一般图像匹配方法运算量大、耗时长的缺点，满足实际运用中匹配精度和速度的要求。