Committee ChairSundareshan, Malur K.
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PublisherThe University of Arizona.
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.
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.
Degree ProgramElectrical and Computer Engineering