Development of Image Preprocessing Methods for Software Compensation of Refraction Anomalies of an Observer’s Eyes

The routine practice of presenting various static and video images to users by means of the digital, processor- controlled, and generally self-illuminating devices (computer monitors, smartphone screens, tablets, etc.) which have become commonplace has spurred the development of various methods for improving the perception of such images by means of computer preprocessing. This also applies to methods of preprocessing images for presentation to users with different refractive errors of the eye (for example, myopia or astigmatism) in situations in which they are not provided with glasses or other corrective devices. Over a period of more than 20 years, researchers have published dozens of works addressing this problem, which is known as the precompensation problem. We take the view that the time has come to consider the development of scientific thought in this direction and highlight the most important milestones in a) understanding the problems that stand in the way of achieving “ideal” precompensation and b) approaches to their successful solution. The first part of this review addresses these issues. The second part focuses on the current state of research in this area, highlighting problems remaining to be solved and trying to capture trends in further development of image precompensation methods, paying maximal attention to neural network approaches.