采用加权最小二乘准则的影像仪自动对焦方法

针对影像测量领域中自动对焦方法存在的对焦准确性不高、对焦过程复杂等问题,提出了一种采用加权最小二乘准则的自动对焦方法.首先,根据不同种类图像清晰度评价函数的评价特性,选定对焦过程中所用的图像清晰度评价函数.其次,在图像清晰度评价函数的基础上进行两阶段对焦,即粗对焦阶段与精对焦阶段.然后,分析了加权最小二乘准则中加权系数的确定原则并给出了其具体确定方法.最后,对精对焦阶段所得清晰度评价值进行归一化处理,采用加权最小二乘准则进行高斯曲线拟合求取极值,极值位置即最终正焦平面.实验结果表明:在步距为0.1mm的条件下,该方法与现有的洛伦兹(Lorent)、Gauss拟合方法相比,对焦误差由0.05 mm降低到0.02 mm,有效地提高了现有曲线拟合法的对焦准确性.

Auto-focusing Method of Imaging Instrument by Using Weighted Least Squares Criterion

For the poor accuracy and complicated process of auto-focusing method in vision measuring, an auto-focusing method by using weighted least squares criterion is proposed in this paper. First, according to the evaluation characteristics of different types of image-clarity evaluation function, the image-clarity evaluation function used in the process of auto-focusing is selected. Secondly, on the basis of the selected image-clarity evaluation function, there are two stage of auto-focusing, namely rough and fine auto-focusing; then, the principle of determining the weighted coefficient in the weighted least square criterion is analyzed, and the specific method of the weighting coefficient is given. Finally, the value of image-clarity evaluation function of fine auto-focusing stage is normalized. and the weighted least squares is used to obtain the extreme point of Gaussian curve fitting, and the position of extreme point is regard as the ultimately positive focal plane. Experimental result shows that under the condition of step distance of 0.1mm, compared with the existing curve fitting method such as Lorentz curve fitting and Gaussian curve fitting, the proposed method can reduce the focus error from 0.05mm to 0.02mm, and effectively improve the focusing accuracy of existing curve fitting method.