自动聚焦是图像测量和计算机视觉中的重要技术。研究发现,以前的一些自动聚焦算法,在没有噪声的影响下,效果较好,但一旦有噪声的影响,算法可能会失效,因此,提出了一种自适应的自动聚焦方法。首先通过一个基于局部小窗口的自适应门限将边缘像素和非边缘像素区别开来,然后再加上一个全局门限来进一步滤除噪声的影响,最后用一些自动聚焦算法来计算经过自适应处理后的图像,画出它们的聚焦曲线。经过大量的实验,结果表明,该算法不仅具有单峰性强,无偏性好,灵敏度高等特点,而且还具有很好的抗噪声性能。

Autofocusing is an important technology in the measurement of images and computer vision. After careful experiments, it is found that some conventional autofocusing algorithms are valid without the influence of the noise. However, they will be invalid in the influence of noise. So, an auto-adaptive algorithm to autofocusing is proposed. At first, edge pixels are separated from nonedge pixels by an adaptive threshold in small local area. The global threshold is adapted to eliminate the influence of noise further. Finally, images are computed with some autofocusing method carefully, which are calculated by the adaptive method. At the same time, the focusing curves are plotted. Experiments show that the method not only owns the characteristics of good unbias, clear single apex and high sensitivity and so on, but also has strong performance of antinoise.