基于改进量子遗传算法的红外图像检测研究

Infrared image detection based on improved QGA

为了解决QGA算法在检测红外图像中出现收敛速度慢、易陷入局部极值的问题,提出一种改进算法。首先采用动态策略调整量子门旋转角度,对方向进行调整,通过定义位影响因子和差距度量函数,使得基因位的更新更加快速高效;引入染色体交叉机制,通过对收敛因子、适应度因子和变异加速因子的操作,维护群体的稳定性与多样性,使优良个体朝更优方向进化,提高全局寻优能力。实验仿真结果表明,本文算法检测效果理想,运行速度快,适合实时应用。

In order to solve QGA algorithm in detecting infrared image appear in slow convergence speed, easy to fall into the local extremum, proposed an improved algorithm. Firstly by using dynamic strategy adjustment quantum gate rotation Angle, Then the direction, by defining a adjust impact factor and gap measuring methods, which make a more rapid genetic update efficiency; Then introduce the chromosome cross mechanism and that of convergence factors, fitness factor and mutation accelerated factor of operation, to safeguard the stability and the diversity of population to improve individual in a more excellent optimal direction into and improve global optimization ability. The simulation results through different algorithms for comparison, this paper detected effect ideal, fast operation, suitable for real-time applications.