Research On Pre-correction Algorithm Of Human Eye Diopter For Head Mounted Display Images Based On Deconvolution Filtering

Human ability to interact with graphical user interfaces(GUI)is dependent on clear vision.However,refractive errors such as myopia,hyperopia or astigmatism,can degrade the image quality showed in the human retina.The degradation of image quality results in poor visual effects when interacting effectively with a computer.Besides,our country has over 300 million myopia patients,account for 33% of total myopia patients,more than the world average value.Therefore,the low vision population for vision correction has become our country and the world urgently needs to solve the problem.However,traditional visual correction methods such as glasses and refractive surgery,may result in fatigue and discomfort when viewed for a long time after visual correction of population with low vision,so suitable for low vision population of the human eye diopter's pre-correction algorithm has become an important research topic in the domain of visual information.This article first through a novel blind measurement method based on the subjective visual perception measures the wave-front aberration of human eye.Then,the human eye diopter's pre-correction algorithm based on deconvolution filtering is applied to generate the pre-correction image,and for how to raise the contrast of the pre-correction image using an image contrast enhance method based on total variation.Finally,a helmet is served as displayer to the original image and pre-correction image generated by the algorithm conducting the subjective effect evaluation.Evaluation results show that pre-correction algorithm of human eye diopter for head mounted display images based on deconvolution filtering generated pre-correction image than the original image is clear,namely the low vision population visual clarity has improved.