In order to realize infrared image target detection, this paper focuses on infrared image preprocessing, background suppression and image segmentation. In preprocessing, gray scale grading is used to adjust the weights of gray scale transformation; in the background suppression, the size of Top-hat transforms filter operator is adjusted according to the imaging distance; in image segmentation, the intercept histogram is constructed by referring to the relevant idea of threshold division in two-dimensional gray scale histogram, and the optimal threshold segmentation is calculated according to the criterion of maximum inter-class variance. Ultimately infrared image fast target detection is achieved. This method has the ability of noise suppression, and achieves a good infrared target detection effect on single target and multi-target, and has a certain application prospect of good accuracy.