Publications related to Fast orthogonal sparse approximation algorithms over local dictionaries

Multi-Graph Learning of Spectral Graph Dictionaries

We study the problem of learning constitutive features for the effective representation of graph signals, which can be considered as observations collected on different graph topologies. We propose to learn graph atoms and build graph dictionaries that pro ...

2015

Transformation-Invariant Dictionary Learning for Classification with 1-Sparse Representations

Pascal Frossard, Elif Vural, Ahmet Caner Yüzügüler

Sparse representations of images in well-designed dictionaries can be used for effective classification. Meanwhile, training data available in most realistic settings are likely to be exposed to geometric transformations, which poses a challenge for the de ...

2014

LAYOUT ASSESSMENT METHOD AND SYSTEM

Frank Grégoire Jean de Morsier, Virginia Estellers Casas, Nathalie Casati, Maria Gabrani

Candidate layout patterns can be assessed using a sparse pattern dictionary of known design layout patterns by determining sparse coefficients for each candidate pattern, reconstructing the respective candidate pattern, and determining reconstruction error ...

U.S. Patent and Trademark Office; U.S. DEPARTMENT OF COMMERCE2013

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

Learning of Structured Graph Dictionaries

Pascal Frossard, Xiaowen Dong, Xue Zhang

We propose a method for learning dictionaries towards sparse approximation of signals defined on vertices of arbitrary graphs. Dictionaries are expected to describe effectively the main spatial and spectral components of the signals of interest, so that th ...

2012

Ultrasound Tomography with Learned Dictionaries

Martin Vetterli, Pascal Frossard, Ivana Tosic, Ivana Jovanovic

We propose a new method for imaging sound speed in breast tissue from measurements obtained by ultrasound tomography (UST) scan- ners. Given the measurements, our algorithm finds a sparse image representation in an overcomplete dictionary that is adapted t ...

2010

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

Sparsity & [and] dictionaries - algorithms & [and] design

Karin Schnass

With the flood of information available today the question how to deal with high dimensional data/signals, which are cumbersome to handle, to calculate with and to store, is highly important. One approach to reducing this flood is to find sparse signal rep ...

EPFL2009

A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

Pierre Vandergheynst, Rémi Gribonval

We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift- invariant signal dictionaries with localized atoms, such as time-frequency dictionaries, and achieves a ...

2009

Algorithms and methods for sparse approximation in structured dictionaries

Lorenzo Peotta

In the last decade we observed an increasing interaction between data compression and sparse signals approximations. Sparse approximations are desirable because they compact the energy of the signals in few elements and correspond to a structural simplific ...

EPFL2007

Fast orthogonal sparse approximation algorithms over local dictionaries

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Multi-Graph Learning of Spectral Graph Dictionaries

Transformation-Invariant Dictionary Learning for Classification with 1-Sparse Representations

LAYOUT ASSESSMENT METHOD AND SYSTEM

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

Learning of Structured Graph Dictionaries

Ultrasound Tomography with Learned Dictionaries

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

Sparsity & [and] dictionaries - algorithms & [and] design

A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

Algorithms and methods for sparse approximation in structured dictionaries

Learning of Structured Graph Dictionaries

Multi-Graph Learning of Spectral Graph Dictionaries

Transformation-Invariant Dictionary Learning for Classification with 1-Sparse Representations

Algorithms and methods for sparse approximation in structured dictionaries

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

LAYOUT ASSESSMENT METHOD AND SYSTEM

Sparsity & [and] dictionaries - algorithms & [and] design

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

A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

Ultrasound Tomography with Learned Dictionaries