Because infrared image has the characteristics of low contrast and low signal-to-noise ratio, it is necessary to be enhanced. A second-generation wavelet transform based infrared image nonlinear enhancement algorithm is presented. The method is adopted to decompose the input infrared image, which extracts multi-scale detail features of the image. Then, according to the difference between target and background noise signal, a fuzzy nonlinear enhancement operator is used to enhance the details of target feature intensity under different scale. Finally, the inverse transform of wavelet is applied to reconstruct image. The algorithm can avoid over-enhanced noise and raise image contrast. Compared with other several image enhancement algorithms, several groups of experimental results demonstrate that the presented algorithm enhance content information the infrared images target effectively.