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In this paper, we have summarized the necessary statistical theory behind an image reconstruction, and it discusses the idea of super resolution as an inverse problem. Moreover, it presents the various contributions of various techniques to improve spatial resolution of images, video, and magnetic resonance images using super resolution methods. Subsequently, it portrays the major findings pertaining to the study. Additionally, we give a glimpse of the numerous factors influencing the performance of super resolution.

Magnetic resonance imaging (MRI) is the preferred imaging modality for visualization of intracranial soft tissues. Surgical planning and, increasingly, surgical navigation use high-resolution three-dimensional patient-specific structural maps of the brain. Such maps are commonly provided by pre-operatively acquired MRI scans, stereo-tactically co-registered with a rigid frame attached to the head of the patient. This paper illustrates magnetic resonance techniques such as fast MRI, spiral imaging, and parallel imaging. Subsequently, image quality evaluation techniques for magnetic resonance images and the perceptual difference models are discussed.

Super-resolution is the process of reconstructing a high-resolution magnetic resonance image (MRI) sequence from one or many low-resolution MRI sequences. In MRI, low-resolution images are usually interpolated to reduce the voxel size and enhance the perceptible resolution. Conventional interpolation methods are not able to recover the high-frequency information lost during the acquisition process. In this manuscript a novel super-resolution technique is proposed for the recovery of such information using coplanar high-resolution images. The proposed methodology benefits from the fact that in typical clinical settings both high- and low-resolution images of different types are taken of the same subject. These available high-resolution images can be used to enhance the resolution of other coplanar lower resolution images. Experiments on MRI data are described to show the efficacy of the proposed approach. An evaluation with conventional interpolation techniques is presented to illustrate the superior performance of the proposed methodology relative to preceding techniques.