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Author Almeida, Mariana S. C. ♦ Figueiredo, Mário A. T.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Unknown Blur ♦ Direction Method ♦ Ill-posed Inverse Problem ♦ New Version ♦ Inverse Problem ♦ Real Blurred Image ♦ Wide Range ♦ Original Image ♦ Unknown Boundary Condition ♦ State-of-the-art Speed ♦ Real-world Bid Problem ♦ Much Interest ♦ Non-cyclic Deconvolution ♦ Index Term ♦ Optimization Tool ♦ Optimization Problem ♦ Prior Knowledge ♦ Restoration Quality ♦ Recent Approach ♦ Realistic Case ♦ State-of-the-art Performance ♦ Blurring Filter ♦ Unknown Image ♦ Blind Image
Abstract Blind image deblurring (BID) is an ill-posed inverse problem, typically solved by imposing some form of regularization (prior knowledge) on the unknown blur and original image. A recent approach, although not requiring prior knowledge on the blurring filter, achieves state-of-the-art performance for a wide range of real-world BID problems. We propose a new version of that method, in which both the optimization problems with respect to the unknown image and with respect to the unknown blur are solved by the alternating direction method of multipliers (ADMM) – an optimization tool that has recently sparked much interest for solving inverse problems, namely due to its modularity and state-of-the-art speed. Our approach also handles seamlessly the realistic case of blind deblurring with unknown boundary conditions. Experiments with synthetic and real blurred images show the competitiveness of the proposed method, both in terms of speed and restoration quality. Index Terms — Blind deblurring, blind deconvolution, alternating direction method of multipliers, non-cyclic deconvolution.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study