基于Roberts梯度的自动聚焦算法

Auto-focusing algorithm based on Roberts gradient

如何快速有效地实现聚焦一直是图像测量中的焦点,其中图像自动聚焦评价函数的选择是关键问题。在比较、研究图像聚焦评价函数和边缘检测的基础上,提出了将Roberts梯度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,仔细研究阈值问题,并引入了一个阈值参数。经过大量的仿真实验,画出了几种自动聚焦算法的聚焦图形,并进行了详细的比较分析。结果表明,引入参数的Roberts算子具有无偏性好、单峰性强、灵敏度高等特点,该算子比其他评价函数更为准确、稳定、可靠。

How to realize the auto-focusing rapidly and efficiently is a focus in the measurement of images. The key problem is to select the auto-focusing evaluation function for images. In this paper, some well-known auto-focusing and edge detection algorithms were compared and investigated, then the auto-focusing evaluation function of the Roberts gradient was proposed. In order to eliminate the influence of noise, the problem of threshold was studied carefully, and a threshold parameter was introduced. After detailed experiments, some focused forms for several auto-focusing algorithms were drown,and at one time,the results were analyzed and compared carefully,and show that the Roberts algorithms have the characteristics of the threshold parameter unbiased, powerful single apex and high sensitive and so on, and are more accurate, stable and reliable.