对含光源等过亮区域场景的自动对焦较为常见, 这些区域导致了图像像素的饱和, 然而所提出的现有的评价函数适用于一般场景, 无法适用于像夜景光源的场景。针对这一问题, 通过分析饱和像素在离焦过程中的特性, 提出了一种去除饱和像素的图像清晰度评价方法, 且其可以用于评估包含光源或者过亮区域场景的图像质量。通过对大津法进行修改得到对焦窗口二值图, 并利用形态学膨胀手段扩展饱和像素区域, 以防止其在离焦过程中产生弥散, 得到去除饱和像素区域的模板, 将其作用于梯度信息矩阵, 计算得到去除饱和像素影响的平均梯度值作为自动对焦评价函数。通过多组离焦序列图测试了所提出的评价函数, 并与其他4种常用的评价函数进行比较, 结果表明, 此自动对焦评价函数适用于含有光源等过亮区域场景的拍摄, 具有良好的无偏性、单峰性、稳定性且覆盖范围较广。

The autofocus of the scenes containing high bright areas such as light sources is common and the high brightness areas lead to saturation of the image pixels. However, the existing evaluation functions are put forward for normal scenario and these cannot be applied for the scenes with light sources such as the nightscop. A sharpness evaluation function is proposed to remove saturate pixels by analyzing the performance of scenes including light sources in the process of defocus and it can be used to evaluate the image quality of scenes containing light sources or high bright areas. A binary map of focusing window is acquired by modifying the Ostu algorithm, and an expansion region of high bright areas is obtained by morphological expansion method to prevent the dispersion of bright areas caused by defocus blur. The removed bright areas template is put on the gradient information matrix, and the average gradient is used as sharpness evaluation value index. The sharpness evaluation index is tested using multiple sets of focal sequence diagram. The results demonstrate that the proposed autofocus evaluation function is applicable to the scenes containing light sources or high bright areas compared with other four common evaluation functions. The proposed method has favorable unbiasedness, unimodality, stability and broad coverage.