和声量子遗传算法在图像配准中的应用

Application of harmony search quantum genetic algorithm in image registration

针对图像配准中的优化问题,利用量子遗传算法全局寻优能力强以及和声算法的微调特性,提出了一种新的和声量子遗传算法(harmony search quantum genetic algorithm,HSQGA)。并将其应用到航拍图像配准当中。仿真结果证明了该算法比原有的和声算法和量子遗传算法在图像配准参数优化过程中具有更好的优化性能。此外,利用两个标准基本测试函数对新算法进行了测试,结果表明在一定的迭代次数内,该算法对一些复杂的优化问题也能精确寻优。

A new harmony search quantum genetic algorithm（HSQGA） is proposed for image registration, in which the harmony search （HS） method is merged together with the quantum genetic algorithm （QGA）. The proposed algorithm is employed in parameter optimization of aerial image registration, and it can yield a superior optimization performance over the original HS method and basic QGA. The proposed algorithm is further tested on two common test functions, and simulation results illustrate that the proposed algorithm can find good solu- tions in the limited number of iteration.