Infrared detection is widely used in the field of infrared small target detection due to its strong penetration, long detection distance and good concealment. In this paper, an infrared small target detection method based on dual-enhanced local contrast measurement is proposed on the basis of the local contrast method of human visual mechanism. Firstly, the noise and background are suppressed by local gray mean contrast, followed by target enhancement by a combination of relative grey scale gradient and local variance contrast, and the infrared small target is detected by threshold segmentation finally. The algorithm has higher detection rate and lower false alarm rate for different sky scene sequences, the former is up to 100%, and the latter is 0. The target detection performance of the same complex scene is significantly improved compared with other similar methods, signal-to-clutter ratio gain and background suppression factor are also significantly improved, resulting in excellent target detection performance.