Jian Huang 1 , Armando Barreto 1 , Miguel Alonso Jr. 2 , Malek Adjouadi 1 1 Electrical and Computer Engineering Department, Florida International University, Miami, FL, 33174 USA 2 School of Computer & Engineering Technologies, Miami-Dade College, Miami, FL, 33176 USA Abstract—Many computer users suffer varying degrees of visual impairment, which hinder their interaction with computers. In contrast with available methods of vision correction (spectacles, contact lenses, LASIK, etc.), this paper proposes a vision correction method for computer users based on image pre-compensation. The blurring caused by visual aberration is counteracted through the pre-compensation performed on images displayed on the computer screen. The pre-compensation model used is based on the visual aberration of the user’s eye, which can be measured by a wavefront analyzer. However, the aberration measured is associated with one specific pupil size. If the pupil has a different size during viewing of the pre-compensated images, the pre-compensation model should also be modified to sustain appropriate performance. In order to solve this problem, an adjustment of the wavefront function used for pre-compensation is implemented to match the viewing pupil size. The efficiency of these adjustments is evaluated with an “artificial eye” (high resolution camera). Results indicate that the adjustment used is successful and significantly improves the images perceived and recorded by the artificial eye. Index Terms—Vision Correction, Point Spread Function (PSF), Deconvolution, Pupil Size, Wavefront Transformation. I. INTRODUCTION ISUAL perception in humans can be described as a process that transmits image information from the physical world to the brain by sensing the intensity and color of light. It is a critical means to acquire knowledge since it provides us with rich and direct information about our surroundings. A good visual perception is also necessary for Human-Computer interaction. However, the human eye may have imperfections, which include various visual aberrations. If uncorrected, these aberrations will cause the image formed on the user’s retina to be blurred or distorted. Therefore, without vision correction, it will be difficult for these users to interact with computers efficiently. Traditionally, vision correction is mainly achieved by spectacles and contact lenses. Laser vision correction, such as LASIK and LASEK, has also become popular recently. However, spectacles and contact lenses are only effective to correct low-order aberrations, and laser vision correction needs to change the shape of the cornea permanently to compensate the overall aberration of the human eye. All these vision correction methods achieve the correction by changing characteristics of the optical path between the object viewed and the retina. In this paper, a vision correction method in which the correction takes place at the source of a computer image is proposed. Aiming to improve the visual performance of computer users with visual impairments, this method achieves the correction by performing pre-compensation of the images before they are displayed on the computer screen. The pre-compensation is performed to counteract the blurring and distortion caused by visual aberrations in the user’s eye and seeks the perception of undistorted images by the user. The pre-compensation model used in this method is based on the visual aberration of the user’s eye, which can be measured by a wavefront analyzer. However, the aberration measured is associated with one specific pupil size. This is because the aberration is usually represented as a set of Zernike coefficients which must be defined on a specific radius. However, in practice the pupil size of a human eye may vary due to accommodation or the change of illumination. In addition, pupil size also depends on other factors such as emotional factors and attentional factors [1], [2]. Therefore, the pre-compensation model can be inaccurate if it is based on a constant pupil size. Thus, readjustment of the pre-compensation model is necessary to ensure the model is matched to the pupil size at viewing. A number of approaches [3], [4], [5] have been developed to recalculate the new set of Zernike coefficients when the pupil size changes. In this paper, the transformation method proposed by Campbell [5] is used to adapt the pre- compensation model from the original one to a new one corresponding to a new pupil size. We also test the efficiency of this adaptation using an “artificial eye” implemented with a high resolution camera. A. Wavefront Aberration Most human eyes have varying degrees of aberration. The wavefront aberration function, used to describe the refraction characteristic of the eye, is defined as the difference between the actual aberrated wavefront and the ideal spherical wavefront of light coming into the eye. Any wavefront aberration will degrade the resulting retinal images. B. Zernike Polynomials The wavefront aberration is usually decomposed into a set of basis functions and represented as a set of coefficients. The value of each coefficient indicates the amount of that particular aberration (e.g., defocus, astigmatism, coma, etc.). The most popular set of basis functions to represent wavefront aberration is the Zernike polynomials. The Vision Correction for Computer Users Based on Image Pre- Compensation with Changing Pupil Size V