A Perceptually Reweighted Mixed-Norm Method for Sparse Approximation of Audio Signals

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Abstrakt

In this paper, we consider the problem of finding sparse representations of audio signals for coding purposes. In doing so, it is of utmost importance that when only a subset of the present components of an audio signal are extracted, it is the perceptually most important ones. To this end, we propose a new iterative algorithm based on two principles: 1) a reweighted l1-norm based measure of sparsity; and 2) a reweighted l2-norm based measure of perceptual distortion. Using these measures, the considered problem is posed as a constrained convex optimization problem that can be solved optimally using standard software. A prominent feature of the new method is that it solves a problem that is closely related to the objective of coding, namely rate-distortion optimization. In computer simulations, we demonstrate the properties of the algorithm and its application to real audio signals.
OriginalsprogEngelsk
TidsskriftAsilomar Conference on Signals, Systems and Computers. Conference Record
Sider (fra-til)575-579
Antal sider5
ISSN1058-6393
DOI
StatusUdgivet - 2011
BegivenhedAsilomar Conference on Signals, Systems and computers, Nov. 6-9, 2011 - Pacific Grove, USA
Varighed: 6 nov. 20119 nov. 2011

Seminar

SeminarAsilomar Conference on Signals, Systems and computers, Nov. 6-9, 2011
LandUSA
ByPacific Grove
Periode06/11/201109/11/2011

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