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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 gradformat@asu.edu.


The technological advances in the past few decades have made possible creation and consumption of digital visual content at an explosive rate. Consequently, there is a need for efficient quality monitoring systems to ensure minimal degradation of images and videos during various processing operations like compression, transmission, storage etc. Objective Image Quality Assessment (IQA) algorithms have been developed that predict quality scores which match well with human subjective quality assessment. However, a lot of research still remains to be done before IQA algorithms can be deployed in real world systems. Long runtimes for one frame of image is a major …

Contributors
Yadav, Aman, Sohoni, Sohum, Aukes, Daniel, et al.
Created Date
2016

The information era has brought about many technological advancements in the past few decades, and that has led to an exponential increase in the creation of digital images and videos. Constantly, all digital images go through some image processing algorithm for various reasons like compression, transmission, storage, etc. There is data loss during this process which leaves us with a degraded image. Hence, to ensure minimal degradation of images, the requirement for quality assessment has become mandatory. Image Quality Assessment (IQA) has been researched and developed over the last several decades to predict the quality score in a manner that …

Contributors
Gunavelu Mohan, Aswin, Sohoni, Sohum, Ren, Fengbo, et al.
Created Date
2017

Image processing has changed the way we store, view and share images. One important component of sharing images over the networks is image compression. Lossy image compression techniques compromise the quality of images to reduce their size. To ensure that the distortion of images due to image compression is not highly detectable by humans, the perceived quality of an image needs to be maintained over a certain threshold. Determining this threshold is best done using human subjects, but that is impractical in real-world scenarios. As a solution to this issue, image quality assessment (IQA) algorithms are used to automatically compute …

Contributors
Gupta, Ayush, Sohoni, Sohum, Amresh, Ashish, et al.
Created Date
2017