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    block this user Michael Elad Trusted member

    Professor

    Technion - Israel institute of Technology

    K-SVD: Design of dictionaries for sparse representation

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    In recent years there is a growing interest in the study of sparse representation for signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Recent activity in this field concentrated mainly on the study of pursuit algorithms that decompose signals with respect to a given dictionary. In this paper we propose a novel algorithm – the K-SVD algorithm – generalizing the K-Means clustering process, for adapting dictionaries in order to achieve sparse signal representations. We analyze this algorithm and demonstrate its results on both synthetic tests and in applications on real data.

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    Title : K-SVD: Design of dictionaries for sparse representation
    Abstract : In recent years there is a growing interest in the study of sparse representation for signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Recent activity in this field concentrated mainly on the study of pursuit algorithms that decompose signals with respect to a given dictionary. In this paper we propose a novel algorithm – the K-SVD algorithm – generalizing the K-Means clustering process, for adapting dictionaries in order to achieve sparse signal representations. We analyze this algorithm and demonstrate its results on both synthetic tests and in applications on real data.
    Subject : unspecified
    Area : Engineering
    Language : English
    Affiliations : 
    Url : http://www.cs.technion.ac.il/~elad/publications/conferences/2005/31_KSVD_SPARSE.pdf
    Doi : 10.1.1.99.4103

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