Document Type
Thesis
Degree
Master of Science (MS)
Major/Program
Computer Engineering
First Advisor's Name
Armando Barreto
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Malek Adjouadi
Third Advisor's Name
Frank Candocia
Date of Defense
4-4-2003
Abstract
Traditional Optics has provided ways to compensate some common visual limitations (up to second order visual impairments) through spectacles or contact lenses. Recent developments in wavefront science make it possible to obtain an accurate model of the Point Spread Function (PSF) of the human eye. Through what is known as the "Wavefront Aberration Function" of the human eye, exact knowledge of the optical aberration of the human eye is possible, allowing a mathematical model of the PSF to be obtained. This model could be used to pre-compensate (inverse-filter) the images displayed on computer screens in order to counter the distortion in the user's eye.
This project takes advantage of the fact that the wavefront aberration function, commonly expressed as a Zernike polynomial, can be generated from the ophthalmic prescription used to fit spectacles to a person. This allows the pre-compensation, or onscreen deblurring, to be done for various visual impairments, up to second order (commonly known as myopia, hyperopia, or astigmatism). The technique proposed towards that goal and results obtained using a lens, for which the PSF is known, that is introduced into the visual path of subjects without visual impairment will be presented. In addition to substituting the effect of spectacles or contact lenses in correcting the loworder visual limitations of the viewer, the significance of this approach is that it has the potential to address higher-order abnormalities in the eye, currently not correctable by simple means.
Identifier
FI13101605
Recommended Citation
Alonso, Miguel, "On-screen pre-deblurring of digital images using the wavefront aberration function of the human eye to improve computer access for the visually impaired" (2003). FIU Electronic Theses and Dissertations. 1111.
https://digitalcommons.fiu.edu/etd/1111
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