High resolution image reconstruction from digital video by exploitation of non-global motion

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 have been suggested in the literature such as microscanning. Here we propose an algorithm to include the possibility of non-global motion. We show that the motion of rigid objects within the scene is often sufficient to up-sample the object. The experimental results presented illustrate the breakdown of global reconstruction algorithms in the presence of non-global rigid motion. We also present results using the proposed method that treats individual moving objects and background separately. The results include data from an infrared detector.