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Variational Image Restoration
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Leah Bar
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Thursday, 10.1.2008, 11:00
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EE Meyer Building 1061
This research concerns the image deblurring and noise removal problem in a variational framework. Energy functionals in this study consist of a fidelity term and a regularizer that is based on Mumford-Shah segmentation, such that the recovered image and its discontinuities set are simultaneously extracted in the course of the deblurring process. We first consider the image deblurring problem in the presence of Gaussian/impulsive noise and present a convergence result for the numerical scheme. Then, we extend the deblurring and denoising problem to vector-valued images. Further, we present the semi- blind shift-variant deblurring case followed by simultaneous motion estimation and restoration of motion-blurred video.
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