摘要
针对平面样品的大规模显微图像采集,提出了一种基于预测的快速自动对焦算法。首先,利用相邻图像的对焦位置估计当前图像的对焦位置,并在其附近做微小调整即可得到最佳对焦位置,从而避免对焦评价曲线的多峰干扰。其次,利用阈值分割方法选择对焦窗口以消除背景干扰,使对焦评价函数满足无偏性。该算法大大减少了自动对焦所需要采集的图像数量,对焦速度、精度以及鲁棒性均有明显的提高。
A fast autofocusing algorithm based on prediction is proposed for the large-scale microscopic images acquisition of flat preparations. Firstly,the method uses the in-focus positions of adjacent images to estimate that of current images, and then makes tiny adjustment at the estimated position to get accurate in-focus position,thus,avoids the local maxima problem of focusing curves. Secondly, the global threshold method is used to select focusing window adaptively, and it can eliminate the background interference and ensure the accuracy of focusing curves. This algorithm decreases greatly the number of images that are acquired for autofocusing,and increases the speed,accuracy and robustness of the microscopic autofocusing sys tem.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2007年第1期9-12,共4页
Journal of Optoelectronics·Laser
基金
国家自然科学基金资助项目(60272042)
关键词
自动对焦对焦函数
线性预测
对焦窗口
autofocusing
focus function
automatic microscope
linear prediction
focusing window
