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20072026
most citedA Proximal Decomposition Method for Solving Convex Variational Inverse Problems

208 citations · 1.7k across the 69 of their papers we have counts for

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Showing 2011Show all

5 papers · 1 filter

math.OC2011★ 120 cited

A Majorize-Minimize subspace approach for l2-l0 image regularization

Emilie Chouzenoux, Anna Jezierska, Jean-Christophe Pesquet +1

In this work, we consider a class of differentiable criteria for sparse image computing problems, where a nonconvex regularization is applied to an arbitrary linear transform of th…

math.ST2011★ 30 cited

Noise Covariance Properties in Dual-Tree Wavelet Decompositions

Caroline Chaux, Jean-Christophe Pesquet, Laurent Duval

Dual-tree wavelet decompositions have recently gained much popularity, mainly due to their ability to provide an accurate directional analysis of images combined with a reduced red…

math.OC2011★ 2 cited

Primal-dual splitting algorithm for solving inclusions with mixtures of composite, Lipschitzian, and parallel-sum monotone operators

Patrick L. Combettes, Jean-Christophe Pesquet

We propose a primal-dual splitting algorithm for solving monotone inclusions involving a mixture of sums, linear compositions, and parallel sums of set-valued and Lipschitzian oper…

cs.OH2011★ 23 cited

Relaxing Tight Frame Condition in Parallel Proximal Methods for Signal Restoration

Nelly Pustelnik, Jean-Christophe Pesquet, Caroline Chaux

A fruitful approach for solving signal deconvolution problems consists of resorting to a frame-based convex variational formulation. In this context, parallel proximal algorithms a…

stat.ME2011

4D Wavelet-Based Regularization for Parallel MRI Reconstruction: Impact on Subject and Group-Levels Statistical Sensitivity in fMRI

Lotfi Chaari, Sébastien Mériaux, Solveig Badillo +2

Parallel MRI is a fast imaging technique that enables the acquisition of highly resolved images in space. It relies on -space undersampling and multiple receiver coils with comp…