This paper describes a new detection approach for small moving objects in noisy image sequences. This algorithm consists of pre-detection and post-detection. The pre-detection algorithm uses a multiple-median filter and an adaptive thresholding to suppress background clutter and enhance small targets. Where an estimate of the local clutter and noise are first done, the clutter and noise estimate are then subtracted from the primary image data to yield residuals that are potential targets. Finally the adaptive thresholding is used to turn residual images into binary images. Post-detection is performed on the binary image sequences. The only a priori information required in the post-detection technique is the maximum velocity of objects in sequence images. It uses the temporal continuity of the trajectories of moving targets to enhance the probability of detection and suppresses the probability of false alarm. Some results on two-dimensional infrared image sequences are presented.