If a point on an object passes over two or more photoreceptors during image acquisition, a blur will occur. Under these conditions, an object or scene is said to move fast relative to the camera's ability to capture the motion. In this work, we consider the iterative restoration of images blurred by distinct, fast moving objects in the frames of a (video) image sequence. Even in the simplest case of fast object motion, the degradation is spatially variant with respect to the image scene. Rather than segmenting the image into regions where the degradation can be considered space invariant, we allow the blur to vary at each pixel and perform iterative restoration. Our approach requires complete knowledge of the blur point spread function (PSF) to restore the scene. The blur of fast moving object in a single frame is under specified. With the appropriate assumptions, an estimate of the blur PSF can be specified to within a constant scaling factor using motion information provided by a displacement vector field (DVF). A robust iterative restoration approach is followed which allows for the incorporation of prior knowledge of the scene structure into the algorithm to facilitate the restoration of difficult scenes. A bilinear approximation to the continuous PSF derived from the motion estimate is proposed to obtain results for real and synthetic sequences. We found this approach suitable for restoring motion degradations in a wide range of digital video applications. The results of this work reinforced the well known flexibility of the iterative approach to restoration and its application as an off-line image sequence restoration method.