In order to improve the accuracy of infrared small target detection,the hysteresis threshold segmentation is proposed for threshold segmentation of small targets.It pre-extracts the central pixel of the infrared small target by fast non-maximum suppression,minimizes the foreground pixel number.The neighborhood gradient variance is used to decide whether the small target is clutter.The gray threshold is then adjusted adaptively,and the small target is segmented with lower false alarm probability.Based on the analysis of the components of foreground and background in the general scene,the threshold value for the small target segmentation is given.Experiments show that the hysteresis threshold segmentation method limits the false alarm probability to a small range and achieves a detection probability superior to other segmentation methods.On the small target detection,the algorithm has strong practicability.