针对传统调焦函数对噪声敏感和调焦范围小从而影响自动对焦准确性的问题，提出了一种基于变频梯度的自动对焦评价函数。解决了由于离焦量过大而引起的评价函数调焦范围小的问题，通过改变采样频率实现了评价函数调焦范围的可调性。其中，评价函数采用了带有阈值选取的梯度绝对值算子，提高了评价函数的抗噪性，降低了时间复杂度。分别利用仿真实验和实拍实验对该方法进行验证，实验表明：采用不同采样频率的梯度算子能够兼顾调焦范围广以及灵敏度高的两种特性，并与现有的对焦评价函数进行了比较，通过量化指标说明了该评价函数的运算速度较现有评价函数有较大的提升，证明了所提出方法抗噪性与实时性更好、灵敏度更高、调焦范围可调，同时能够准确评价离焦图像清晰度。“,”In the existing automatic focusing systems, the traditional evaluation functions are sensitive to noise and have small focusing range which will affect the accuracy of the auto-focusing results. An autofocus evaluation function based on gradient operator with variable frequency was proposed. It solved the problem that the coverage of the evaluation functions is small when the fuzzy degree is larger by sampling frequency reducing method in the image space. As mentioned above, an absolute value gradient operator with threshold value selection was adopted, which not only improved the noise resistance but also reduced the complexity. Then, the simulation experiments and actual tests were carried out to validate the satisfactory performance of the method. The experimental results indicate that it can meet the characteristics of wide focusing range and high sensitivity at the same time when the gradient operator with different sampling frequencies was used and then compared with the existing traditional methods. The quantitative indicators were used to illustrate that the calculation speed of the evaluation function were improved a lot compared with the existing evaluation function. The autofocus evaluation function proposed was demonstrated has better anti-noise performance and has variable focusing range with high sensitivity and high real-time, which can evaluate the sharpness degree of the images in the process of automatic focus accurately.