应用于聚焦窗口自适应选择的人工鱼群算法改进

聚焦窗口选择是自动聚焦算法中的重要模块,直接影响评价函数曲线的尖锐性、精确性,影响聚焦系统的复杂度。针对传统的聚焦区域选择算法的局限性,提出了一种基于AFSA的聚焦区域自适应选择算法;针对标准的人工鱼群算法易陷入局部最优的缺陷,对人工鱼群算法中的参数设置及行为进行改进。实验表明,采用人工鱼群算法可快速实现效果较好的前景图像分割,通过选取前景边缘丰富的区域,保证了前景聚焦的精确性;算法可以跟踪偏离中心的主体景物,适用于主体与背景对比度小的情况,因此得到的聚焦区域是动态的,具有自适应性。

Application of artificial fish swarm algorithm on adaptive auto-focusing window selection

Window selection is an important module of autofocusing system（AF）,which directly impacts the sharpness and accuracy of focusing evaluation curve and the complexity of AF system.It can reduce the processing data and increase the focus speed;it can also weaken the impact of non-interest region and improve the focus accuracy.For the traditional window selection algorithms have some limitations,an algorithm based on artificial fish swarm algorithm（AFSA） is proposed;because the standard AFSA falls into local optimum easily,the parameters’setting and behavior are improved in this paper.Experi- ment results show that foreground image can be segmented accurately using this method.The proposed method can track the main object and be applicable to images with small contrast,so the window is dynamic with good adaptability.