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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- Partial requirement for: Ph.D., Arizona State University, 2016Note typethesis
- Includes bibliographical references (pages 92-103)Note typebibliography
- Field of study: Electrical engineering