基于全自动控制显微镜的自动聚焦算法研究  

Study on Auto Focusing Algorithm for Automatic Microscope

作　　者：姜志国[1] 韩冬兵[1] 袁天云[1] 赵宇[1] 谢凤英[1] 陈进[2] 

机构地区：[1]北京航空航天大学宇航学院图象中心,北京100083 [2]麦克奥迪实业集团有限公司,厦门361006

出　　处：《中国图象图形学报（A辑）》2004年第4期396-401,共6页Journal of Image and Graphics

基　　金：国家自然科学基金项目(60372017)

摘　　要：图像自动聚焦评价函数的选择是全自动控制显微镜无源方式自动聚焦系统的关键问题。对几种主要的图像聚焦评价函数 (灰度方差算子、灰度梯度算子、能量谱方法等 )进行了比较、研究 ,并在此基础上首次将改进的 L aplacian算子作为聚焦评价函数引入自动聚焦之中 ,同时为了消除噪声的影响 ,引入了步长和阈值两个参数。实验结果表明 ,改进的L aplacian算子比其他评价函数更为准确、稳定和可靠 。Choosing auto focusing evaluation function for images is a key factor for passive auto focusing system of automatic microscope. The basic requirements for a practical auto focusing system are speed, sharpness and robustness to noise. With the relationship between focused and defocused images of a scene, some well known focusing measures (such as gradation variance operator, gradation gradient operator and energy spectrum measure) have been investigated. Based on them, a sum modified Laplacian (SML) operator has been proposed as focusing measures for the first time. The operator is applied to measure the relative sharpness of image sequence at different object distances. Step and threshold are introduced to effectively alleviate the effect of the noise. All of the above mathematical models have been analyzed and compared. Experimental results are presented that demonstrate the accuracy and robustness of the proposed method. The results show that the SML operator is more accurate, stable and reliable than other auto focusing evaluation functions for microscopy images. The algorithm has been applied successfully to automatic focusing system of microscope and testified to be feasible and effective.

关 键 词：自动聚焦 全自动显微镜 评价函数 LAPLACIAN算子 噪声 

分 类 号：TH742[机械工程—光学工程]