In the infrared imaging system, the low-frequency nonuniformity noise will seriously affect the imaging effect of the infrared system, and the low-frequency dark circle or dark spot is the nonuniformity noise radiated by the optical lens and camera shell, which seriously affects the imaging quality of the infrared imaging system, so it needs to be corrected by the nonuniformity correction technology. However, due to the influence of time and other factors, the traditional calibration method will change the original correction parameters, which will lead to the inability to effectively remove the low-frequency nonuniformity noise, resulting in the degradation of the imaging quality of the infrared imaging system. The main research content of this paper is to use the nonuniformity correction technology based on single frame infrared image to correct the image of infrared imaging system, restore the scene content of the original infrared image to the greatest extent, improve the image quality, and do the basic work for other image processing steps later. This paper first analyzes the sources of low-frequency nonuniformity noise, then introduces several mainstream low-frequency nonuniformity noise correction algorithms based on single frame image at home and abroad, and points out the characteristics of these algorithms. According to the limitations of these algorithms, two nonuniformity correction algorithms based on single frame image are proposed, which make the iterative least square calculation based on improved bilateral filtering respectively Method and nonuniformity correction algorithm based on wavelet filter kernel and difference information. In the first method, the noisy image is first processed by difference, then the high frequency scene information is suppressed by the optimized bilateral filtering algorithm, and then the parameters of the noise model are obtained by the iterative least square method. In the second method, firstly, the noisy image is filtered by wavelet to suppress the high-frequency information, then the L1 regularization energy functional of non-uniform noise is established by using the sparse characteristics of scene and noise gradient information, and finally the surface parameters are obtained by using the alternating direction multiplier method to solve the optimization problem, thus the low-frequency non-uniform noise image is obtained.