The small infrared target detection methods used in the presence of background interference and noises are analyzed. A small infrared target detection algorithm combining temporal domain with spatial domain is put forward. First, the interference from background and noises is reduced by using conjoint frame subtraction because of the slow change of background. Then, the nonsubsampled Contourlet transform is implemented for the residual image so as to eliminate the residual background and noises and enhance the signal-to-noise ratio of the small targets. Finally, the enhanced image is processed by using the adaptive threshold and the small target is detected. The simulation result shows that compared with the small infrared target detection algorithm based on wavelet transform, this method can more precisely detect small infrared targets and has a higher detection effectiveness and a lower average false alarm rate.