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New Signal Processing Methods for Blur Detection and Applications

Abstract 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 input image is proposed. Quantitative results expressed ... (more)
Created Date 2019
Contributor Andrade Rodas, Juan Manuel (Author) / Spanias, Andreas (Advisor) / Turaga, Pavan (Advisor) / Abousleman, Glen (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Blur detection / Defocus / No-reference image quality assessment / Objective blur assessment / spatially varying
Type Doctoral Dissertation
Extent 102 pages
Language English
Note Doctoral Dissertation Electrical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis