We propose a reconstruction scheme adapted to MRI that takes advantage of a sparsity constraint in the wavelet domain. We show that artifacts are significantly reduced compared t...
Matthieu Guerquin-Kern, Dimitri Van De Ville, C&ea...
Algorithms based on the minimization of the Total Variation are prevalent in computer vision. They are used in a variety of applications such as image denoising, compressive sensi...
Much research has been devoted to the problem of restoring Poissonian images, namely for medical and astronomical applications. However, the restoration of these images using state...
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
We present a new algorithm for bound-constrained totalvariation (TV) regularization that in comparison with its predecessors is simple, fast, and flexible. We use a splitting app...