Year: 2018
East Asian Journal on Applied Mathematics, Vol. 8 (2018), Iss. 3 : pp. 586–597
Abstract
A variational $ℓ_q$-seminorm model to reduce the impulse noise is proposed. For $0<q<1$, it captures sparsity better than the $ℓ_1$-norm model. Numerical experiments show that for small $q$ this model is more efficient than TV$ℓ_1$ model if the noise level is low. If the noise level grows, the best possible parameter $q$ in the model approaches 1.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.101117.130418
East Asian Journal on Applied Mathematics, Vol. 8 (2018), Iss. 3 : pp. 586–597
Published online: 2018-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 12
Keywords: Impulse noise sparsity ℓq-seminorm total variation iterative reweighted algorithm.