Thursday, 10.1.2008, 11:00
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