Medical imaging is one of the important and challenging areas of research in the field of image processing. Medical images play an important role in the field of medical science by giving support to the diagnostic process of a disease and in suggesting the treatment. Medical images produced by different acquisition devices are not of very high resolution and they require a very deep and critical analysis to diagnose a disease. In our work we have addressed the problem of very low resolution by improving the spatial quality of the images by applying super resolution (SR). Process of SR is further composed of two steps, namely image registration and image reconstruction. We have targeted Medical Resonance (MR) images and improved their spatial resolution, because MR is more capable of capturing the details of soft tissues. Our proposed algorithm consists of phases which deal with the image both in the spatial domain as well as the frequency domain. We have used the demons deformable image registration algorithm in the image registration phase and wavelet based method for image reconstruction. After reconstruction various qualitative and quantitative measures have been applied on the images. These measures clearly support the claim that the proposed technique has improved the visibility of 58% of the images, such that, reconstructed high resolution images have more resolving power as compared to the low resolution input images.