High-frame-rate imaging technique, such as Corneal Visualization Scheimpug Technology, plays an important role in evaluating corneal properties. Many studies measure various biomechanical parameters and associate them to different corneal pathological conditions. However, the vertical resolution of the acquired images is limited mainly due to optical distortions and acquisition errors, which in some scenarios (where sufficient vertical resolution is critical) mislead the interpretation and clinical diagnosis of corneal pathological conditions therefore it become critical to establish an efficient way to improve the vertical resolution in Scheimpflug photography. In this work, we propose an effective computational method to retrieve the image details in high-frame-rate imaging, providing both high temporal and vertical resolution. Experiments and a utility assessment including image data from totally 120 subjects on the measurement of central corneal thickness demonstrate a previously-not-recognized pattern of corneal deformation in air puff tests, as well as the statistically significant difference revealed (p < 0.01) between normal and keratoconus subject groups from the super-resolved time series. The proposed approach is preliminarily proven to be a useful tool for a finer characterization of the cornea.