Rafael Eduardo Carrillo Rangel

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In the context of next generation radio telescopes, like the Square Kilometre Array, the efficient processing of large-scale datasets is extremely important. Convex optimisation tasks under the compressive sensing framework have recently emerged and provid ...

Ultrafast imaging based on plane-wave (PW) insonification is an active area of research due to its capability of reaching high frame rates. Among PW imaging methods, Fourier-based approaches have demonstrated to be competitive compared to traditional delay ...

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bispectrum measurements. We reformulate this nonlin- ear problem as a linear problem for the supersymmetric rank-1 order-3 tensor ...

Next generation radio telescopes, like the Square Kilometre Array, will acquire an unprecedented amount of data for radio astronomy. The development of fast, parallelisable or distributed algorithms for handling such large-scale data sets is of prime impor ...

Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for electrocardiogram (ECG) monitoring. However, the performance of current CS-based algorithms, in terms of c ...

Ultrafast imaging based on plane-wave (PW) in- sonification is an active area of research due to its capability of reaching high frame rates. Several approaches have been proposed either based on either of Fourier-domain reconstruction or on delay-and-sum ...

Empirical mode decomposition (EMD) is a multiresolution data analysis method recently developed to cater to the inherent nonstationarity in real-world signals. A two-dimensional (2D) extension of EMD is used in this paper as a pavement distress image analy ...

While compressive sensing (CS) has traditionally relied on L2 as an error norm, a broad spectrum of applications has emerged where robust estimators are required. Among those, applications where the sampling process is performed in the presence of impulsiv ...

In recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this talk, I will review our latest contribut ...

We propose a novel regularization method for compressive imaging in the context of the CS theory with coherent and redundant dictionaries. The approach relies on the conjecture that natural images exhibit strong average sparsity over multiple coherent fram ...

Compressive sensing generally relies on the L2-norm for data fidelity, whereas in many applications robust estimators are needed. Among the scenarios in which robust performance is required, applications where the sampling process is performed in the prese ...

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 ...

Recent developments in [1] and [2] introduced a novel regularization method for compressive imaging in the con- text of compressed sensing with coherent redundant dictionaries. The approach relies on the observation that natural images exhibit strong avera ...

According to recent studies, Latin America is the region with the highest emigration rate in the world, specially affecting the highly educated population. One of the consequences of this process is the expansion of business and scientific diasporas. Colom ...

Ultrafast ultrasound (US) imaging based on plane wave (PW) insonification is a widely used modality nowadays. Two main types of approaches have been proposed for image reconstruction either based on classical delay-and-sum (DAS) or on Fourier reconstructio ...

We study the impact of the spread spectrum effect in radio interferometry on the quality of image reconstruction. This spread spectrum effect will be induced by the wide ﬁeld-of-view of forthcoming radio interferometric telescopes. The resulting chirp modu ...

OBJECTIVE The authors developed a new, real-time interactive inverse planning approach, based on a fully convex framework, to be used for Gamma Knife radiosurgery. ...

We propose a novel algorithm for source signals estimation from an underdetermined convolutive mixture assuming known mixing filters. Most of the state-of-the-art methods are dealing with anechoic or short reverberant mixture, assuming a synthesis sparse p ...

In a recent article series, the authors have promoted convex optimization algorithms for radio-interferometric imaging in the framework of compressed sensing, which leverages sparsity regularization priors for the associated inverse problem and defines a m ...

Rafael Eduardo Carrillo Rangel

Chat with Graph Search

Scalable splitting algorithms for big-data interferometric imaging in the SKA era

A sparse reconstruction framework for Fourier-based plane wave imaging

Tensor optimisation for optical-interferometric imaging

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems

A sparse regularization approach for ultrafast ultrasound imaging

Multiresolution Information Mining for Pavement Crack Image Analysis

An overview of robust compressive sensing of sparse signals in impulsive noise

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Sparsity averaging for radio-interferometric imaging

A scalable algorithm for radio-interferometric imaging

Robust compressive sensing of sparse signals: A review

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

On Sparsity Averaging

iNVESTIGA: Connecting the Colombian Scientific Diaspora with Secondary Schools in Colombia

Sparse regularization methods in ultrafast ultrasound imaging

The varying w spread spectrum effect for radio interferometric imaging

A real-time optimal inverse planning for Gamma Knife radiosurgery by convex optimization: description of the system and first dosimetry data

Sparse Reverberant Audio Source Separation via Reweighted Analysis

PURIFY: a new approach to radio-interferometric imaging