Many imaging systems utilize detector arrays that do not sample the scene according to the Nyquist criterion. As a result, the higher spatial frequencies admitted by the optics are aliased. This creates undesirable artifacts in the imagery. Furthermore, the blurring effects of the optics and the finite detector size also degrade the image quality. Several approaches for increasing the sampling rate of imaging systems have been suggested in the literature. We propose an algorithm for resolution enhancement that exploits object motion in digital video sequences. Unlike previously defined techniques, we use an automated segmentation method to isolate rigid moving objects. These are accurately registered and the multiple observations of the object are used to produce an effectively high sampling rate over the object. The experimental results presented illustrate the breakdown of resolution enhancement algorithms that assume global scene motion when the actual scene motion is nonglobal. The performance of the proposed algorithm is illustrated using images from a forward looking IR imager and a visible range camera.