基于最大梯度和阈值的自动聚焦算法

Auto-focusing Algorithm Based on Most Gradient and Threshold

目前,国内外有很多基于梯度的自动聚焦算法,但是它们都是用指定的方向去求梯度,但真实梯度方向可能不是它们的指定的方向;另外,当图像受到噪声污染的时候,算法的稳定性也不好。为了解决以上问题,提出了一种基于最大梯度的自动聚焦算法。首先,对任意可能的梯度方向都求出它的梯度,比较后得到最大的梯度,利用最大的梯度作为最后的结果。同时,考虑到算法的精确度和稳定性,再引入了阈值参数。经过实验表明,该算法具有单峰性强、无偏性好、灵敏度高、稳定性好等特点。

At present, there are a lot of auto-focusing algorithms based on gradient both in domestic and oversea. However, when they calculate the gradient, they get the gradient value only in appointed fixed directions, but the real gradient direction may not be the appointed direction, so there is some error. In addition, when the images are polluted by noise, the stability of the auto-focusing algorithm is reduced. In order to solve these problems, an auto-focusing algorithm based on the most gradient and threshold is proposed. At first, we calculate the gradients in all possible directions, then compare all of the possible gradients, and choose the largest gradient as the result. At the same time, in order to improve the precision and stability of auto-focusing algorithm, we introduce another threshold parameter. Through careful experiments, we find out that the algorithm has the characteristics such as good unbiased characteristic, strong single peak feature, high sensitivity and good stability and so on.