Publication

Experimental validation of a bayesian model of visual acuity

Dalimier, E.
; 
Pailos, E.
; 
Rivera, R.
; 
Navarro, R.
Repository DOI
Publication Date
2009-07-01
Keywords
vision modeling, pattern recognition, ocular aberrations, best refraction, visual acuity, retinal image quality, living human eye, monochromatic aberrations, chromatic aberrations, contrast sensitivity, optical aberrations, pupil centration, wave aberrations, adaptive optics, performance
Type
Article
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Citation
Dalimier, E. Pailos, E.; Rivera, R.; Navarro, R. (2009). Experimental validation of a bayesian model of visual acuity. Journal of Vision 9 (7),
Abstract
Based on standard procedures used in optometry clinics, we compare measurements of visual acuity for 10 subjects (11 eyes tested) in the presence of natural ocular aberrations and different degrees of induced defocus, with the predictions given by a Bayesian model customized with aberrometric data of the eye. The absolute predictions of the model, without any adjustment, show good agreement with the experimental data, in terms of correlation and absolute error. The efficiency of the model is discussed in comparison with image quality metrics and other customized visual process models. An analysis of the importance and customization of each stage of the model is also given; it stresses the potential high predictive power from precise modeling of ocular and neural transfer functions.
Funder
Publisher
Association for Research in Vision and Ophthalmology (ARVO)
Publisher DOI
10.1167/9.7.12
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Externally hosted open access publications with University of Galway authors (2)