TY - JOUR T1 - An $ℓ_q$ - Seminorm Variational Model for Impulse Noise Reduction AU - Yoon Mo Jung, Taeuk Jeong & Sangwoon Yun 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 -
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.