Publications associées à Joint Sparsity with Partially Known Support and Application to Ultrasound Imaging

Metric Learning with Rank and Sparsity Constraints

Volkan Cevher, Baran Gözcü, Bubacarr Bah

Choosing a distance preserving measure or metric is fun- damental to many signal processing algorithms, such as k- means, nearest neighbor searches, hashing, and compressive sensing. In virtually all these applications, the efficiency of the signal process ...

Ieee2014

Fast and robust estimation of jointly sparse channels

Martin Vetterli, Ali Hormati, Yann Barbotin

A device and method for estimating multipath jointly sparse channels. The method comprises receiving a number K of signal components by a number P of receiving antennas, where P≧2. The method further comprises estimating the sparsity condition of the multi ...

2013

Anisotropic Interpolation of Sparse Generalized Image Samples

Michaël Unser, Aurélien Bourquard

Practical image-acquisition systems are often modeled as a continuous-domain prefilter followed by an ideal sampler, where generalized samples are obtained after convolution with the impulse response of the device. In this paper, our goal is to interpolate ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Joint Low-rank and Sparse Light Field Modeling for Dense Multiview Data Compression

Pierre Vandergheynst, Mahdad Hosseini Kamal

The effective representation of the structures in the multiview images is an important problem that arises in visual sensor networks. This paper presents a novel recovery scheme from compressive samples which exploit local and non-local correlated structur ...

2013

Joint Low-Rank And Sparse Light Field Modelling For Dense Multiview Data Compression

Pierre Vandergheynst, Mahdad Hosseini Kamal

Ieee2013

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Pascal Frossard, Pierre Vandergheynst, Adel Rahmoune

This paper introduces a novel algorithm for sparse approximation in redundant dictionaries called the M-term pursuit (MTP). This algorithm decomposes a signal into a linear combination of atoms that are selected in order to represent the main signal compon ...

Institute of Electrical and Electronics Engineers2012

Methods and systems for noise resilient, pin-efficient and low power communications with sparse signaling codes

Mohammad Amin Shokrollahi, Seyed Armin Tajalli, Harm Cronie

In bus communications methods and apparatus, a first set of physical signals representing the information to be conveyed over the bus is provided, and mapped to a codeword of a sparse signaling code, wherein a codeword is representable as a vector of a plu ...

2012

Hard Thresholding with Norm Constraints

Volkan Cevher, Gilles Puy, Anastasios Kyrillidis

We introduce a new sparse recovery paradigm, called Normed Pursuits, where efficient algorithms from combinatorial and convex optimization interface for interpretable and model-based solutions. Synthetic and real data experiments illustrate that Normed Pur ...

Ieee2012

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Joint Sparsity with Partially Known Support and Application to Ultrasound Imaging

Metric Learning with Rank and Sparsity Constraints

Fast and robust estimation of jointly sparse channels

Anisotropic Interpolation of Sparse Generalized Image Samples

Joint Low-rank and Sparse Light Field Modeling for Dense Multiview Data Compression

Joint Low-Rank And Sparse Light Field Modelling For Dense Multiview Data Compression

Compressive Sampling Strategies for Multichannel Signals

Distributed Compressed Representation of Correlated Image Sets

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Methods and systems for noise resilient, pin-efficient and low power communications with sparse signaling codes

Hard Thresholding with Norm Constraints

Graph Chatbot

Chattez avec Graph Search

Joint Low-rank and Sparse Light Field Modeling for Dense Multiview Data Compression

Distributed Compressed Representation of Correlated Image Sets

Methods and systems for noise resilient, pin-efficient and low power communications with sparse signaling codes

Hard Thresholding with Norm Constraints

Anisotropic Interpolation of Sparse Generalized Image Samples

Metric Learning with Rank and Sparsity Constraints

Compressive Sampling Strategies for Multichannel Signals

Fast and robust estimation of jointly sparse channels

Joint Low-Rank And Sparse Light Field Modelling For Dense Multiview Data Compression

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding