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Related publications (77)

A Practical Inverse-Problem Approach to Digital Holographic Reconstruction

Michaël Unser, Christian Depeursinge, Nicolas Pavillon, Emrah Bostan, Aurélien Bourquard

In this paper, we propose a new technique for high-quality reconstruction from single digital holographic acquisitions. The unknown complex object field is found as the solution of a nonlinear inverse problem that consists in the minimization of an energy ...

OSA2013

Eigensensing And Deconvolution For The Reconstruction Of Heat Absorption Profiles From Photoacoustic Tomography Data

Dimitri Nestor Alice Van De Ville, Thierry Blu, Zafer Dogan

Photoacoustic tomography (PAT) is a relatively recent imaging modality that is promising for breast cancer detection and breast screening. It combines the high intrinsic contrast of optical radiation with acoustic imaging at submillimeter spatial resolutio ...

Ieee2013

Sparse Stochastic Processes and Discretization of Linear Inverse Problems

Michaël Unser, Emrah Bostan, Ulugbek Kamilov, Masih Nilchian

We present a novel statistically-based discretization paradigm and derive a class of maximum a posteriori (MAP) estimators for solving ill-conditioned linear inverse problems. We are guided by the theory of sparse stochastic processes, which specifies cont ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Sampling and reconstructing diffusion fields in presence of aliasing

Martin Vetterli, Juri Ranieri

The reconstruction of a diffusion field, such as temperature, from samples collected by a sensor network is a classical inverse problem and it is known to be ill-conditioned. Previous work considered source models, such as sparse sources, to regularize the ...

2013

Laplacian Meshes for Monocular 3D Shape Recovery

Pascal Fua, Aydin Varol, Tien Dat Ngo, Jonas Olof Martin Östlund

We show that by extending the Laplacian formalism, which was first introduced in the Graphics community to regularize 3D meshes, we can turn the monocular 3D shape reconstruction of a deformable surface given correspondences with a reference image into a w ...

2012

Differential Phase-Contrast X-Ray Computed Tomography: From Model Discretization To Image Reconstruction

Michaël Unser, Masih Nilchian

Our contribution in this paper is two fold. First, we propose a novel discretization of the forward model for differential phase-contrast imaging that uses B-spline basis functions. The approach yields a fast and accurate algorithm for implementing the for ...

Ieee2012

Differential Phase-Contrast x-Ray Computed Tomography: From Model Discretization to Image Reconstruction

Michaël Unser, Masih Nilchian

IEEE2012

Sparsity Averaging Reweighted Analysis (SARA): a novel algorithm for radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

We propose a novel algorithm for image reconstruction in radio interferometry. The ill-posed inverse problem associated with the incomplete Fourier sampling identified by the visibility measurements is regularized by the assumption of average signal sparsi ...

Wiley-Blackwell2012

A Real-Time Deformable Detector

Pascal Fua, François Fleuret, Karim Ali, David Hasler

We propose a new learning strategy for object detection. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform base ...

Institute of Electrical and Electronics Engineers2012

The importance of priors for l2 regularization and total variation methods in quantitative susceptibility mapping

Rolf Gruetter, Yves Wiaux, José Pedro Rebelo Ferreira Marques, Gilles Puy, Diana Khabipova

Phase imaging has been demonstrated to offer a good contrast between and within brain tissues at 7T[1] with iron and myelin concentration being amongst the main modulators of the observed contrast due to their para- and dia-magnetic properties.Phase imagin ...

2012

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