Spatially non-uniform blur analysis based on wavelet transform
Date of Award
2010
Degree Name
M.S. in Electrical Engineering
Department
Department of Electrical and Computer Engineering
Advisor/Chair
Advisor: Keigo Hirakawa
Abstract
Object motion causes spatially varying blur in an image. Partial blur typically carries useful information about the scene. This information is useful for consumer imaging as well as computer vision. However, spatially varying blur also deteriorates image quality. The goals of our research are finding out this information and making images better. In this thesis we introduce a novel method for solving this partial blur problem. We define a statistical model of a spatially-varying blur image and estimate the local point spread function (PSF) by using a set of methods including double wavelet transform and local autocorrelation. Experimental results demonstrate the effectiveness of the proposed algorithm.
Keywords
Image reconstruction Mathematical models, Wavelets (Mathematics), Image processing Mathematical models, Autocorrelation (Statistics), Image reconstruction
Rights Statement
Copyright © 2010, author
Recommended Citation
Zhang, Yi, "Spatially non-uniform blur analysis based on wavelet transform" (2010). Graduate Theses and Dissertations. 294.
https://ecommons.udayton.edu/graduate_theses/294
