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Communication Dans Un Congrès Année : 2011

Single image local blur identification

Résumé

We present a new approach for spatially varying blur identification using a single image. Within each local patch in the image, the local blur is selected between a finite set of candidate PSFs by a maximum likelihood approach. We propose to work with a Generalized Likelihood to reduce the number of parameters and we use the Generalized Singular Value De- composition to limit the computing cost, while making proper image boundary hypotheses. The resulting method is fast and demonstrates good performance on simulated and real examples originating from applications such as motion blur identification and depth from defocus.
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Dates et versions

hal-00732435 , version 1 (14-09-2012)

Identifiants

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Pauline Trouvé, Frédéric Champagnat, Guy Le Besnerais, Jérôme Idier. Single image local blur identification. 2011 18th IEEE International Conference on Image Processing (ICIP), Sep 2011, Bruxelles, Belgium. pp.613 - 616, ⟨10.1109/ICIP.2011.6116625⟩. ⟨hal-00732435⟩
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