TY - JOUR
T1 - An $ℓ_q$ - Seminorm Variational Model for Impulse Noise Reduction
JO - East Asian Journal on Applied Mathematics
VL - 3
SP - 586
EP - 597
PY - 2018
DA - 2018/08
SN - 8
DO - http://doi.org/10.4208/eajam.101117.130418
UR - https://global-sci.org/intro/article_detail/eajam/12627.html
KW - Impulse noise, sparsity, ℓq-seminorm, total variation, iterative reweighted algorithm.
AB - <p style="text-align: justify;">A variational $ℓ_q$-seminorm model to reduce the impulse noise is proposed. For $0&lt;q&lt;1$, 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.</p>