在航空遥感图像复原过程中，系统调制传递函数(Modulation Transfer Function, MTF)测量是非常重要的一步。刀刃法因具有很多优点而成为测量MTF中较常见的方法。利用刀刃法测量红外相机MTF时，边缘扩散函数(Edge Spread Function, ESF)的提取和拟合非常关键，这直接决定了后续MTF计算效果的好坏。实验设计了一种新的提取边缘数据点的方法。该方法通过移动刃边来直接观察单个像元灰度值的变化，比利用遥感图像获得ESF的传统方法要简单、直观。同时，对比了线性拟合、高斯拟合与费米拟合三种ESF曲线拟合方法的效果。结果表明，费米拟合很好地平滑了ESF两端的噪声，效果最好。

In the process of aviation remote sensing image restoration, the measurement of Modulation Transfer Function (MTF) of a system is very important. Because of many advantages, a knife-edge method becomes a relatively common method for measuring MTF. When using the knife-edge method to measure MTF of an infrared camera, the extraction and fitting of Edge Spread Function (ESF) are critical, which directly determines the effectiveness of subsequent MTF calculation. A new method for extracting edge data points is designed in an experiment. Since the method directly observes the gray-scale variation of a single pixel by moving the knife-edge, it is simpler and more intuitive than the traditional method which obtains ESF from remote sensing images. At the same time, the effectiveness of three fitting methods including linear fitting, Guassian fitting and Fermi fitting is compared. The results show that the Fermi fitting smoothes the noise at each end of ESF nicely and obtains the best result.