ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at email@example.com.
- 3 English
- 2 Electrical engineering
- 1 3D Stereo
- 1 Blur Discrimination
- 1 Blur detection
- 1 Defocus
- 1 Engineering
- 1 Image Distortion
- 1 No-reference image quality assessment
- 1 Objective blur assessment
- 1 Subjective Testing
- 1 Texture Analysis
- 1 Texture Granularity
- 1 Texture Synthesis
- 1 Visual Compresssion
- 1 Visual Saliency
- 1 spatially varying
Blur is an important attribute in the study and modeling of the human visual system. In this work, 3D blur discrimination experiments are conducted to measure the just noticeable additional blur required to differentiate a target blur from the reference blur level. The past studies on blur discrimination have measured the sensitivity of the human visual system to blur using 2D test patterns. In this dissertation, subjective tests are performed to measure blur discrimination thresholds using stereoscopic 3D test patterns. The results of this study indicate that, in the symmetric stereo viewing case, binocular disparity does not affect the blur …
- Subedar, Mahesh, Karam, Lina, Abousleman, Glen, et al.
- Created Date
Visual attention (VA) is the study of mechanisms that allow the human visual system (HVS) to selectively process relevant visual information. This work focuses on the subjective and objective evaluation of computational VA models for the distortion-free case as well as in the presence of image distortions. Existing VA models are traditionally evaluated by using VA metrics that quantify the match between predicted saliency and fixation data obtained from eye-tracking experiments on human observers. Though there is a considerable number of objective VA metrics, there exists no study that validates that these metrics are adequate for the evaluation of VA …
- Gide, Milind Subhash, Karam, Lina J, Abousleman, Glen, et al.
- Created Date
The depth richness of a scene translates into a spatially variable defocus blur in the acquired image. Blurring can mislead computational image understanding; therefore, blur detection can be used for selective image enhancement of blurred regions and the application of image understanding algorithms to sharp regions. This work focuses on blur detection and its application to image enhancement. This work proposes a spatially-varying defocus blur detection based on the quotient of spectral bands; additionally, to avoid the use of computationally intensive algorithms for the segmentation of foreground and background regions, a global threshold defined using weak textured regions on the …
- Andrade Rodas, Juan Manuel, Spanias, Andreas, Turaga, Pavan, et al.
- Created Date