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Real-time l1-l2 deblurring using wavelet expansions of operators

Escande, Paul and Weiss, Pierre Real-time l1-l2 deblurring using wavelet expansions of operators. (2015) Journal of Computational and Applied Mathematics. ISSN 0377-0427 (Unpublished)

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Abstract

Image deblurring is a fundamental problem in imaging, usually solved with computationally intensive optimization procedures. We show that the minimization can be significantly accelerated by leveraging the fact that images and blur operators are compressible in the same orthogonal wavelet basis. The proposed methodology consists of three ingredients: i) a sparse approximation of the blur operator in wavelet bases, ii) a diagonal preconditioner and iii) an implementation on massively parallel architectures. Combing the three ingredients leads to acceleration factors ranging from 30 to 250 on a typical workstation. For instance, a 1024 × 1024 image can be deblurred in 0.15 seconds, which corresponds to real-time.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National des Sciences Appliquées de Toulouse - INSA (FRANCE)
Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Laboratory name:
Funders:
PRES of Toulouse University and Midi-Pyrenees region
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Deposited By: Paul Escande
Deposited On:26 Apr 2017 09:29

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