Two-dimensional bar code out-of-focus deblurring via the Increment Constrained Least Squares filter
Pattern Recognition Letters
Joint MAP estimation for blind deconvolution: when does it work?
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Extensions of the Justen---Ramlau blind deconvolution method
Advances in Computational Mathematics
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In this paper, we propose and present an algorithm for total variation (TV)-based blind deconvolution. Both the unknown image and blur can be estimated within an alternating minimization framework. With the generalized cross-validation (GCV) method, the regularization parameters associated with the unknown image and blur can be updated in alternating minimization steps. Experimental results confirm that the performance of the proposed algorithm is better than variational Bayesian blind deconvolution algorithms with Student's-t priors or a total variation prior.