Publications related to Sparse Approximation Using M-Term Pursuits with Applications to Image and Video Compression

Structured Sparse Coding for Image Denoising or Pattern Detection

Sparsity has been one of the major drives in signal processing in the last decade. Structured sparsity has also lately emerged as a way to enrich signal priors towards more meaningful and accurate representations. In this paper we propose a new structured ...

2014

Quadtree Structured Image Approximation for Denoising and Interpolation

Adam James Scholefield, Pier Luigi Dragotti

The success of many image restoration algorithms is often due to their ability to sparsely describe the original signal. Shukla et al. proposed a compression algorithm, based on a sparse quadtree decomposition model, which could optimally represent piecewi ...

Institute of Electrical and Electronics Engineers2014

A convex optimization framework for global tractography

Jean-Philippe Thiran, Alessandro Daducci, Alia Lemkaddem

In this article we present a novel approach for diffusion MRI global tractography. Our formulation models the signal in each voxel as a linear combination of fiber-tract basis func- tions, which consist of a comprehensive set of plausible fiber tracts that ...

2013

An Iterative Linear Expansion of Thresholds for l1-based Image Restoration

Thierry Blu, Hanjie Pan

This paper proposes a novel algorithmic framework to solve image restoration problems under sparsity assumptions. As usual, the reconstructed image is the minimum of an objective functional that consists of a data fidelity term and an l1 regularization. Ho ...

Institute of Electrical and Electronics Engineers2013

Real-Time High-Precision Reading Algorithm for the Ironless Inductive Position Sensor

Alessandro Danisi, Alessandro Masi

This paper presents a novel reading algorithm for an ironless inductive position sensor which exhibits immunity to single-frequency interference (both for high and low frequency signals). This algorithm is based on the three-parameter sine fitting, whose p ...

Ieee-Inst Electrical Electronics Engineers Inc2013

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

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

Volkan Cevher, Anastasios Kyrillidis

We propose Matrix ALPS for recovering a sparse plus low-rank decomposition of a matrix given its corrupted and incomplete linear measurements. Our approach is a first-order projected gradient method over non-convex sets, and it exploits a well-known memory ...

IEEE2012

Deliverable 3.2: Report on Discovering Structure within Dictionary Learning

In this work package (WP), we investigate the possibility of discovering structure within dictionary learning. This could range from exploring groups of atoms that appear in clusters - a form of molecule learning - to learning graphical dependencies across ...

2011

Dictionary Identification - Sparse Matrix-Factorisation via $\ell_1$-Minimisation

Rémi Gribonval, Karin Schnass

This article treats the problem of learning a dictionary providing sparse representations for a given signal class, via

\ell_1

-minimisation. The problem can also be seen as factorising a

\ddim \times \nsig

matrix $Y=(y_1 \ldots y_\nsig), , y_n\in \R^\ ...

Institute of Electrical and Electronics Engineers2010

Sparse Approximation Using M-Term Pursuits with Applications to Image and Video Compression

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Structured Sparse Coding for Image Denoising or Pattern Detection

Quadtree Structured Image Approximation for Denoising and Interpolation

A convex optimization framework for global tractography

An Iterative Linear Expansion of Thresholds for l1-based Image Restoration

Real-Time High-Precision Reading Algorithm for the Ironless Inductive Position Sensor

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

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

Deliverable 3.2: Report on Discovering Structure within Dictionary Learning

Dictionary Identification - Sparse Matrix-Factorisation via $\ell_1$-Minimisation

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

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

A convex optimization framework for global tractography

Quadtree Structured Image Approximation for Denoising and Interpolation

Deliverable 3.2: Report on Discovering Structure within Dictionary Learning

Real-Time High-Precision Reading Algorithm for the Ironless Inductive Position Sensor

Dictionary Identification - Sparse Matrix-Factorisation via $\ell_1$-Minimisation

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

An Iterative Linear Expansion of Thresholds for l1-based Image Restoration

Structured Sparse Coding for Image Denoising or Pattern Detection