Visual performance prediction using schematic eye models.
The goal of visual modeling is to predict the visual performance or a change in performance of an individual from a model of the human visual system. In designing a model of the human visual system, two distinct functions are considered. The first is the production of an image incident on the retina...
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The University of Arizona.
1995
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ndltd-arizona.edu-oai-arizona.openrepository.com-10150-1873272015-10-23T04:34:19Z Visual performance prediction using schematic eye models. Schwiegerling, James Theodore. Greivenkamp, John Miller, Joseph M. Snyder, Robert W. The goal of visual modeling is to predict the visual performance or a change in performance of an individual from a model of the human visual system. In designing a model of the human visual system, two distinct functions are considered. The first is the production of an image incident on the retina by the optical system of the eye, and the second is the conversion of this image into a perceived image by the retina and brain. The eye optics are evaluated using raytracing techniques familiar to the optical engineer. The effect of the retinal and brain function are combined with the raytracing results by analyzing the modulation of the retinal image. Each of these processes is important far evaluating the performance of the entire visual system. Techniques for converting the abstract system performance measures used by optical engineers into clinically-applicable measures such as visual acuity and contrast sensitivity are developed in this dissertation. Furthermore, a methodology for applying videokeratoscopic height data to the visual model is outlined. These tools are useful in modeling the visual effects of corrective lenses, ocular maladies and refractive surgeries. The modeling techniques are applied to examples of soft contact lenses, keratoconus, radial keratotomy, photorefractive keratectomy and automated lamellar keratoplasty. The modeling tools developed in this dissertation are meant to be general and modular. As improvements to the measurements of the properties and functionality of the various visual components are made, the new information can be incorporated into the visual system model. Furthermore, the examples discussed here represent only a small subset of the applications of the visual model. Additional ocular maladies and emerging refractive surgeries can be modeled as well. 1995 text Dissertation-Reproduction (electronic) http://hdl.handle.net/10150/187327 9620387 en Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. The University of Arizona. |
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en |
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description |
The goal of visual modeling is to predict the visual performance or a change in performance of an individual from a model of the human visual system. In designing a model of the human visual system, two distinct functions are considered. The first is the production of an image incident on the retina by the optical system of the eye, and the second is the conversion of this image into a perceived image by the retina and brain. The eye optics are evaluated using raytracing techniques familiar to the optical engineer. The effect of the retinal and brain function are combined with the raytracing results by analyzing the modulation of the retinal image. Each of these processes is important far evaluating the performance of the entire visual system. Techniques for converting the abstract system performance measures used by optical engineers into clinically-applicable measures such as visual acuity and contrast sensitivity are developed in this dissertation. Furthermore, a methodology for applying videokeratoscopic height data to the visual model is outlined. These tools are useful in modeling the visual effects of corrective lenses, ocular maladies and refractive surgeries. The modeling techniques are applied to examples of soft contact lenses, keratoconus, radial keratotomy, photorefractive keratectomy and automated lamellar keratoplasty. The modeling tools developed in this dissertation are meant to be general and modular. As improvements to the measurements of the properties and functionality of the various visual components are made, the new information can be incorporated into the visual system model. Furthermore, the examples discussed here represent only a small subset of the applications of the visual model. Additional ocular maladies and emerging refractive surgeries can be modeled as well. |
author2 |
Greivenkamp, John |
author_facet |
Greivenkamp, John Schwiegerling, James Theodore. |
author |
Schwiegerling, James Theodore. |
spellingShingle |
Schwiegerling, James Theodore. Visual performance prediction using schematic eye models. |
author_sort |
Schwiegerling, James Theodore. |
title |
Visual performance prediction using schematic eye models. |
title_short |
Visual performance prediction using schematic eye models. |
title_full |
Visual performance prediction using schematic eye models. |
title_fullStr |
Visual performance prediction using schematic eye models. |
title_full_unstemmed |
Visual performance prediction using schematic eye models. |
title_sort |
visual performance prediction using schematic eye models. |
publisher |
The University of Arizona. |
publishDate |
1995 |
url |
http://hdl.handle.net/10150/187327 |
work_keys_str_mv |
AT schwiegerlingjamestheodore visualperformancepredictionusingschematiceyemodels |
_version_ |
1718098147002023936 |