A limitation of scanning laser ophthalmoscopy (SLO) is that eye movements during the capture of each frame distort the retinal image. Various sophisticated strategies have been devised to ensure that each acquired frame can be mapped quickly and accurately onto a chosen reference frame, but such methods are blind to distortions in the reference frame itself. Here we explore a method to address this limitation in software, and demonstrate its accuracy. We used high-speed (200 fps), high-resolution (~1 μm), flood-based imaging of the human retina with adaptive optics to obtain "ground truth" information on the retinal image and motion of the eye. This information was used to simulate SLO video sequences at 20 fps, allowing us to compare various methods for eye-motion recovery and subsequent minimization of intra-frame distortion. We show that a) a single frame can be near-perfectly recovered with perfect knowledge of intra-frame eye motion; b) eye motion at a given time point within a frame can be accurately recovered by tracking the same strip of tissue across many frames, due to the stochastic symmetry of fixational eye movements. This approach is similar to, and easily adapted from, previously suggested strip-registration approaches; c) quality of frame recovery decreases with amplitude of eye movements, however, the proposed method is affected less by this than other state-of-the-art methods and so offers even greater advantages when fixation is poor. The new method could easily be integrated into existing image processing software, and we provide an example implementation written in Matlab.