Description
The quality of real-world visual content is typically impaired by many factors including image noise and blur. Detecting and analyzing these impairments are important steps for multiple computer vision tasks. This work focuses on perceptual-based locally adaptive noise and blur detection and their application to image restoration.
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Contributors
- Zhu, Tong (Author)
- Karam, Lina (Thesis advisor)
- Li, Baoxin (Committee member)
- Bliss, Daniel (Committee member)
- Myint, Soe (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2016
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Note
- Partial requirement for: Ph.D., Arizona State University, 2016Note typethesis
- Includes bibliographical references (pages 92-103)Note typebibliography
- Field of study: Electrical engineering
Citation and reuse
Statement of Responsibility
by Tong Zhu