数字图像散斑相关技术的蚁群优化方法

基于蚁群优化方法提出新的数字图像散斑相关算法。该方法模仿了真实蚂蚁从其巢到食物找到最短路径的方式,通过对蚁群优化方法改进，减少迭代次数并改善解的质量。将新的数字图像散斑相关算法应用到计算机模拟的散斑图像和实验获得的散斑图像中，并与广泛使用的Newton-Raphson算法进行了比较。实验结果展示了新算法的精度、可行性和有效性。当数量级为0.01像素，误差离散均方根小于0.002像素。

New algorithm for digital image speckle correlation method based on ant colony optimization

Based on the ant colony optimization (ACO), a new algorithm for digital image correlation method is proposed. The procedure simulates the way that the real ants find the shortest path from their nest to food source and back. Modifications are made to the ACO algorithm in order to reduce the number of iterations and improve the quality of solutions. The accuracy and efficiency of the new method are demonstrated via application to computer-simulated images and comparison with widely used Newton-Raphson method. The feasibility and validity of the algorithm are also verified through experimentally obtained speckle images. The experimental results demonstrate the performance of our new algorithm.