Variational deblurring of images with uncertain and spatially variant blurs

Authors:
Martin Welk;David Theis;Joachim Weickert
Affiliations:
Mathematical Image Analysis Group, Faculty of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany;Department of Mathematics, Faculty of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany;Mathematical Image Analysis Group, Faculty of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany
Venue:
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Year:
2005

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Abstract

We consider the problem of deblurring images which have been blurred by different reasons during image acquisition. We propose a variational approach admitting spatially variant and irregularly shaped point-spread functions. By involving robust data terms, it achieves a high robustness particularly with respect to imprecisions in the estimation of the point-spread function. A good restoration of image features is ensured by using non-convex regularisers and a strategy of reducing the regularisation weight. Experiments with irregular spatially invariant as well as with spatially variant point-spread functions demonstrate the good quality of the method as well as its stability under noise.