自动对焦
光学(聚焦)
选择(遗传算法)
计算机科学
功能(生物学)
过程(计算)
人工智能
图像(数学)
基点
平面(几何)
计算机视觉
模式识别(心理学)
数学
光学
物理
几何学
进化生物学
生物
操作系统
作者
Meini Lv,Hui Kong Gan,Xin Liu,Jia Chen,Qiuhui Yang
标识
DOI:10.1088/1742-6596/2356/1/012035
摘要
The auto focusing process is affected by the amount of image content, resulting in the focus curve not meeting the characteristics of the ideal focus curve. In this paper, aiming at the problem that the traditional autofocus cannot find the focal plane successfully in the case of microscopic sparse content, the qualitative analysis and quantitative analysis of 12 traditional focus evaluation functions are carried out. The experimental results show that the F Tenengrad function is suitable for the optimal focus evaluation function of sparse microscopic images.
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