Скачать или смотреть Total variation denoising with iterated conditional expectation - Louchet - Workshop 2 - CEB T1 2019

Cécile Louchet (Univ. Orléans) / 12.03.2019

Total variation denoising with iterated conditional expectation.

Imaging tasks most often require an energy minimization interpretable in a probabilistic approach as a maximum a posteriori. Taking instead the expectation a posteriori gives an interesting alternative but confronts the question of numerical integration in high dimension. We propose a variable-at-a-time integration, called after by iterated conditional expectation (ICE), that approximates the expectation a posteriori. We try it on total variation denoising for which it gives good visual properties and linear convergence. We give several clues concerning extensions of the method. Joint work with Lionel Moisan.

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Langue : Anglais; Date : 12.03.2019; Conférencier : Louchet, Cécile; Évenement : Workshop 2 - CEB T1 2019; Lieu : IHP; Mots Clés : denoising, iterated conditional expectation (ICE), expectation a posteriori, total variation, deblurring