变异的粒子群算法在图像分割中的应用

The Application of Particle Swarm Algorithm Based on the Global Optimal Position Mutation in Maximum Entropy Image Segmentation

将粒子群算法和图像分割法相结合,提出了基于全局最优位置变异的粒子群算法的图像分割方法,在保证分割质量的同时,运用算法高效计算的特点,显著地提高了分割速度。本文最后,应用典型函数优化的仿真结果,比对标准粒子群优化算法和本文所提出的改进算法,以证实本文所提出改进算法的优化效果。

The particle swarm algorithm for image segmentation wears combine image segmentation method based on global best position variation of particle swarm algorithm,at the same time ensure the quality of the segmentation,the use of the characteristics of the algorithm for the efficient calculation significantly improve the segmentation speed.Finally, the typical function optimization of simulation results than the standard particle swarm optimization algorithm and the proposed improved algorithm,to confirm the effect of this improved algorithm optimization.