Persistent Link:
http://hdl.handle.net/10150/186468
Title:
Evaluation and optimization of image displays.
Author:
Ji, Ting-Lan.
Issue Date:
1993
Publisher:
The University of Arizona.
Rights:
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.
Abstract:
This dissertation presents procedures for systematic and quantitative evaluations of both physical and psychophysical performance of image display devices. A mathematical expression for the visual luminance response function is derived, which permits developing an optimum display function for display devices. Direct quantitative relations between the physical and the psychophysical parameters are established. It is concluded that in the present state of modern CRTs, the spatial noise due to phosphor granularity offers the major limit to the contrast resolution, and that trying to decrease the spatial noise of a CRT is a more effective approach to increase the perceived dynamic range of the CRT among other considerations. A systematic procedure is developed to optimize the display function such that the contrast information transfer through the display device/human vision system is maximized. The presently derived result indicates that the optimum display function is the inverse of the scaled visual response function determined from the Just-Noticeable-Difference (JND) curve, and is independent of the object size and the noise level (RMS) of the display device. The optimum display function perceptually linearizes the display device in that equal changes in grey level produce changes in luminance that are perceptually equal throughout the entire dynamic range of the display device. This dissertation also presents a novel adaptive contrast enhancement algorithm, called JND-Guided Adaptive Contrast Enhancement (JGACE), to compensate for the limited contrast capability of display devices and to improve the quality of image display. Existing methods for image contrast enhancement focus entirely on the properties of the image to be processed without consideration of the human visual characteristics. The presented algorithm quantitatively achieves an adequate amount of contrast enhancement in terms of the human visual JNDs, and effectively eliminates two common drawbacks of many existing contrast enhancement techniques: ringing artifacts around sharp edges and enhancement of background noise. JGACE can be applied to a variety of images and provides a superior performance compared to previously available techniques. In particular, it offers considerable benefits in digital radiography applications where the objective is to increase the diagnostic utility of images.
Type:
text; Dissertation-Reproduction (electronic)
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Electrical and Computer Engineering; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Sundareshan, Malur K.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleEvaluation and optimization of image displays.en_US
dc.creatorJi, Ting-Lan.en_US
dc.contributor.authorJi, Ting-Lan.en_US
dc.date.issued1993en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © 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.en_US
dc.description.abstractThis dissertation presents procedures for systematic and quantitative evaluations of both physical and psychophysical performance of image display devices. A mathematical expression for the visual luminance response function is derived, which permits developing an optimum display function for display devices. Direct quantitative relations between the physical and the psychophysical parameters are established. It is concluded that in the present state of modern CRTs, the spatial noise due to phosphor granularity offers the major limit to the contrast resolution, and that trying to decrease the spatial noise of a CRT is a more effective approach to increase the perceived dynamic range of the CRT among other considerations. A systematic procedure is developed to optimize the display function such that the contrast information transfer through the display device/human vision system is maximized. The presently derived result indicates that the optimum display function is the inverse of the scaled visual response function determined from the Just-Noticeable-Difference (JND) curve, and is independent of the object size and the noise level (RMS) of the display device. The optimum display function perceptually linearizes the display device in that equal changes in grey level produce changes in luminance that are perceptually equal throughout the entire dynamic range of the display device. This dissertation also presents a novel adaptive contrast enhancement algorithm, called JND-Guided Adaptive Contrast Enhancement (JGACE), to compensate for the limited contrast capability of display devices and to improve the quality of image display. Existing methods for image contrast enhancement focus entirely on the properties of the image to be processed without consideration of the human visual characteristics. The presented algorithm quantitatively achieves an adequate amount of contrast enhancement in terms of the human visual JNDs, and effectively eliminates two common drawbacks of many existing contrast enhancement techniques: ringing artifacts around sharp edges and enhancement of background noise. JGACE can be applied to a variety of images and provides a superior performance compared to previously available techniques. In particular, it offers considerable benefits in digital radiography applications where the objective is to increase the diagnostic utility of images.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairSundareshan, Malur K.en_US
dc.contributor.committeememberSchowengerdt, Robert A.en_US
dc.contributor.committeememberStrickland, Robin N.en_US
dc.identifier.proquest9410669en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.