Super-Resolution (SR) is a technique where a high resolution (HR) image is obtained from a low resolution (LR) image sequence. In SR, the camera scans a scenery to form a mosaic of overlapped image frames. To achieve SR, the relative movement along the low resolution set of images is considered as first step, and later the spatial resolution through data fusion is increased. Resolution increase is important not only for a better image visualization, but also to get additional image details. In the image acquisition process, lenses in cameras induce optics distortions. In the algorithm proposed, the radial distortion is considered. From a priori camera motion information, a Super- Resolution algorithm is proposed. Unlike other algorithms, radial distortion elimination is incorporated. Radial distortion is notably present in low cost sensors. To validate the algorithm, a software system was developed, with real environments and resolution patterns measurements.