Publications related to Structured Sparse Coding for Image Denoising or Pattern Detection

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

Method, apparatus and computer program product for determining the location of a plurality of speech sources

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei

The present invention discloses a method, apparatus and computer program product for determining the location of a plurality of speech sources in an area of interest, comprising performing an algorithm on a signal issued by either one of said plurality of ...

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

Assessing Sparse Coding Methods for Contextual Shape Indexing of Maya Hieroglyphs

Daniel Gatica-Perez, Jean-Marc Odobez, Edgar Roman Rangel

Bag-of-visual-words or bag-of-visterms (bov) is a common technique used to index Multimedia information with the purposes of retrieval and classification. In this work we address the problem of constructing efficient bov representations of complex shapes a ...

2012

Sparse spectral factorization: Unicity and Reconstruction Algorithms

Martin Vetterli, Yue Lu

Spectral factorization is a classical tool in signal processing and communications. It also plays a critical role in X-ray crystallography, in the context of phase retrieval. In this work, we study the problem of sparse spectral factorization, aiming to re ...

2011

A Signal Processing Approach to Generalized 1-D Total Variation

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Ilker Bayram

Total variation (TV) is a powerful method that brings great benefit for edge-preserving regularization. Despite being widely employed in image processing, it has restricted applicability for 1-D signal processing since piecewise-constant signals form a rat ...

Institute of Electrical and Electronics Engineers2011

Trends in Bioimaging and Signal Processing

Michaël Unser

This is the second in a series of three columns summarizing the "Trends" expert sessions organized by the Signal Processing Society Technical Committees during ICASSP 2011 in Prague, Czech Republic. Readers have an opportunity to access these Trends sessio ...

IEEE2011

Direct-Ambient Decomposition and Upmix of Surround Signals

Christof Faller, Andreas Walther

Various direct-ambient signal decompositions, applicable to two-channel stereophonic signals, have been proposed previously. Strategies to enhance these decompositions for multi-channel surround audio signals are not obvious. A method is proposed, which es ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

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

Structured Sparse Coding for Image Denoising or Pattern Detection

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

Method, apparatus and computer program product for determining the location of a plurality of speech sources

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

Assessing Sparse Coding Methods for Contextual Shape Indexing of Maya Hieroglyphs

Sparse spectral factorization: Unicity and Reconstruction Algorithms

A Signal Processing Approach to Generalized 1-D Total Variation

Trends in Bioimaging and Signal Processing

Direct-Ambient Decomposition and Upmix of Surround Signals

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

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

Assessing Sparse Coding Methods for Contextual Shape Indexing of Maya Hieroglyphs

Sparse spectral factorization: Unicity and Reconstruction Algorithms

A Signal Processing Approach to Generalized 1-D Total Variation

Trends in Bioimaging and Signal Processing

Direct-Ambient Decomposition and Upmix of Surround Signals

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

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

Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction

Method, apparatus and computer program product for determining the location of a plurality of speech sources