In practical applications, the traditional adaptive nonuniformity correction algorithm based on Neural Network (NN-NUC) has a limited correction capability and is easy to generate ghosting artifacts. To solve this problem, the ghosting artifact generating process in the NN-NUC algorithm is analyzed in detail and the common methods for removing ghosting artifacts are given. Then, by incorporating the characteristics of actual infrared imagers, an improved NN-NUC algorithm is proposed. The simulation experimental results show that the proposed method can suppress the generation of ghosting artifacts in a scene extremely and can reduce the nonuniformity noise of the image effectively. Moreover, the proposed algorithm has a small calculation amount and is easy to be implemented by hardware. So it is of good value to practical applications.