Vision correction for the visually impaired via digital image processing - Keleş, Onur. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019)
In this study, an adjustment based on the mathematical modeling on digital screens for people with refractive visual impairments is proposed. According to the laws of refraction and diﬀraction, the human eye can be considered as a linear and space-invariant system. In such a case, if the impulse response of the eye (point spread function) is known, the convolution law can determine how the light entering the eye (input) is shaped according to the response of the eye. When the studies using point spread function for this purpose are examined, it is seen that the point spread function of the eye is found only on the basis of the crystalline lens. In this study, the incoming distance of light, the cornea structure, accommodation, age of the person and gradient index structure of the crystalline lens are included in the human eye model. The idea in this study is that, based on the inverse convolution (deconvolution) method, if the light entering the eye is shaped according to the inverse of the impulse response of the eye, theoretically, the patient clearly sees the object whose light comes into the eye. The biggest problem with this approach, which can easily be adapted to personal computers, portable devices and smart glasses that are expected to be developed in the future, is that the deconvolved digital image has a much higher dynamic range than the dynamic range of the standard screens, hence, the disappearance of the necessary contrast. In order to solve this problem, methods that are diﬀerent from studies in the literature are proposed. In the simulations, it is seen that the newly presented methods give better visual results than the existing ones. Although the existing methods are improved with this study, it is suggested as the future work that dynamic range compression and contrast enhancement methods should be further investigated and more complex methods should be proposed.
Keywords: Vision -- Data processing.; Vision -- Mathematical models.; Human information processing.