Visualdistortionandblurringimpedetheefficientinteraction between computers and their users. Visual problems can be caused by eye diseases, severe refractive errors or combinations of both. Several image enhancement methods based on contrast sensitivity have been used to help people with eye diseases e.g., age-related macular degeneration and cataracts whereas few methods have been designed for people with severe refractive errors. This paper describes a new pre-compensation method to counter the visual blurring caused by the severe refractive errors of a specific computer user. It preprocesses the pictorial information through dynamic pre-compensation in advance, aiming to present customized images on the basis of the ocular aberrations of the specific computer user. The new method improves the previous static pre-compensation method by updating the aberration data according to pupil size variations, in real-time. The real-time aberration data enable us to generate better suited pre-compensated images, as the pre-compensation model is updated dynamically. An empirical study was conducted to evaluate the efficiency of the new pre-compensation method, through an icon recognition test. From the results of statistical analysis, we found that participants achieved significantly higher accuracy levels in recognizing the icons with dynamic pre-compensation, than when viewing the original icons. The accuracy is also significantly boosted when the icons were processed with dynamic pre-compensation method, in comparison with the previous static pre-compensation method.