Fast model of space-variant blurring and its application to deconvolution in astronomy

Abstract : Image deblurring is essential to high resolution imaging and is therefore widely used in astronomy, microscopy or com- putational photography. While shift-invariant blur is modeled by convolution and leads to fast FFT-based algorithms, shift- variant blurring requires models both accurate and fast. When the point spread function (PSF) varies smoothly across the field, these two opposite objectives can be reached by inter- polating from a grid of PSF samples. Several models for smoothly varying PSF co-exist in the literature. We advocate that one of them is both physically- grounded and fast. Moreover, we show that the approximation can be largely improved by tuning the PSF samples and inter- polation weights with respect to a given continuous model. This improvement comes without increasing the computa- tional cost of the blurring operator. We illustrate the developed blurring model on a deconvo- lution application in astronomy. Regularized reconstruction with our model leads to large improvements over existing re- sults.
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Contributeur : Ferréol Soulez <>
Soumis le : vendredi 2 septembre 2011 - 15:40:44
Dernière modification le : mardi 18 décembre 2018 - 11:36:01
Document(s) archivé(s) le : mardi 13 novembre 2012 - 09:51:24


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  • HAL Id : hal-00618696, version 1



Loïc Denis, Éric Thiébaut, Ferréol Soulez. Fast model of space-variant blurring and its application to deconvolution in astronomy. ICIP 2011, Sep 2011, Bruxelles, France. pp.2873-2876, 2011. 〈hal-00618696〉



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