基于整体退火遗传算法的柔性形态滤波器优化设计

Optimization Design of Soft Morphological Filters Based on Whole Annealing Genetic Algorithm

整体退火遗传算法 (WAGA)是一种新的遗传算法 ,它将退火机制引入选择算子 ,并允许父代加入竞争 ,使遗传算法更加稳健、高效 .本文应用WAGA优化柔性形态滤波器 ,并研究了在不同噪声比例和最小平均绝对误差(MAE)、最小均方误差 (MSE)准则下优化算法的性能 .仿真实验显示优化后的柔性形态滤波器性能得到较大改善 。

Whole annealing genetic algorithm (WAGA) is a new genetic algorithm.It introduces annealing mechanism to selection operator and allows ancestor to take part in competition,which makes genetic algorithm more robust and efficient.In this paper,we apply WAGA to optimize soft morphological filters and study the performance of optimization algorithm with various noise percentages under MAE or MSE error criteria.The simulation experiments show that optimized soft morphological filters are highly improved and to suit for filtering of noisy images.