MRF-Based blind image deconvolution

Abstract : This paper proposes an optimization-based blind image deconvolution method. The proposed method relies on imposing a discrete MRF prior on the deconvolved image. The use of such a prior leads to a very efficient and powerful deconvolution algorithm that carefully combines advanced optimization techniques. We demonstrate the extreme effectiveness of our method1 by applying it on a wide variety of very challenging cases that involve the inference of large and complicated blur kernels.
Type de document :
Communication dans un congrès
11th Asian Conference on Computer Vision - ACCV 2012, Nov 2012, Daejeon, North Korea. Springer, 7726, pp.361-374, 2012
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https://hal.archives-ouvertes.fr/hal-00856285
Contributeur : Enzo Ferrante <>
Soumis le : vendredi 30 août 2013 - 17:05:50
Dernière modification le : mardi 5 février 2019 - 13:52:14

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  • HAL Id : hal-00856285, version 1

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Nikos Komodakis, Nikos Paragios. MRF-Based blind image deconvolution. 11th Asian Conference on Computer Vision - ACCV 2012, Nov 2012, Daejeon, North Korea. Springer, 7726, pp.361-374, 2012. 〈hal-00856285〉

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