To reduce scanning time and/or improve spatial/temporal resolution in some Magnetic
Resonance Imaging (MRI) applications, parallel MRI acquisition techniques with multiple …

We address the problem of estimating spectral lines from irregularly sampled data within the
framework of sparse representations. Spectral analysis is formulated as a linear inverse …

In this paper, we propose a convex optimization-based estimation of sparse and smooth
power spectral densities (PSDs) of complex-valued random processes from mixtures of …

The paper deals with the construction of images from visibilities acquired using aperture
synthesis instruments: Fourier synthesis, deconvolution, and spectral interpolation …

Complex-valued data are encountered in many application areas of signal and image
processing. In the context of the optimization of functions of real variables, subspace …

Context. The location of pure frequencies in the spectrum of an irregularly sampled time
series is an important topic in astrophysical data analysis. Especially in the domain of …

We propose a method for feature-preserving regularized reconstruction in coherent imaging
systems. In our framework, image formation from measured data is achieved through the …

This paper is a synthetic overview of regularization, maximum entropy and probabilistic
methods for some inverse problems such as deconvolution and Fourier synthesis problems …

We propose a novel depth sensing system composed of a single camera, and a transparent
plate which is placed in front of the camera and rotates about the optical axis of the camera …

The Empirical Mode Decomposition (EMD) is known to be a powerful tool adapted to the
decomposition of a signal into a collection of intrinsic mode functions (IMF). A key procedure …