Development of Image Pre-Processing Methods for Software Compensation of Anomal Refraction of the Observer’s Eyes

Abstract

In recent decades, the practice of demonstrating various static and video images to users using digital, processor-controlled, most often self-luminous devices (computer monitors, smartphone and tablet screens, etc.) has spurred the development of various methods to improve the perception of such images by means of computerized image preprocessing. This also applies to methods of preprocessing images shown to users with various refractive anomalies of the eye(s) (e.g., myopia or astigmatism) in situations where they are not armed with glasses or other corrective devices. Over the past 20+ years, researchers have published dozens of papers on this task, referred to as the precompensation task. In our opinion, the time has come to reflect on the development of scientific thought in this direction and to highlight the most important milestones in realizing the problems on the way to achieving “ideal” precompensation and in approaches to their successful solution. This is the focus of the first part of this review. In the second part, we focus on the current state of research in the stated area, highlight the problems not solved so far, and try to catch the trends of further development of image precompensation methods, paying maximum attention to neural network approaches.