In order to realize segmentation of the IR (infrared) small target image accurately, this paper proposes a segmented algorithm by applying the information entropy method to the infrared image. This paper not only takes the aspect of distribution of gray information into account in the two-dimensional entropy method, but also utilizes fully the spatial neighbor information of the pixel to obtain an ideal effectiveness of segmentation. After the introduction of the maximum entropy method based on the traditional two-dimensional histogram, other two methods based on External 4-connected G-A(Gray level-Average gray level) histogram and the G-G(Gray level-Gray absolute difference) histogram are given and the above methods all work well in the IR small target segmentation. Besides, the bound set of the IR image and the corresponding bound histogram are constructed to narrow the target search scope, and based on its bound histogram the IR image is segmented, by using the above the integer target is obtained with less noise compared with the pure entropy methods. The experiment results show that the algorithm is effective.