Sparsity-driven multiplicative noise reduction
Gülay AKSOY, Fatih Nar · 2017
Speckle noise formed in Synthetic Aperture Radar (SAR) images makes visual and automatic analyses complicated. Thus, reducing speckle noise in homogeneous regions while preserving features such as edges and point scatterers is important as a pre-processing step. Although SAR images predominantly contains multiplicative noise, it also contains low amount of additive noise. In this study, a sparsity-driven multiplicative noise reduction method is proposed that also take additive noise component into account. Performance of the proposed methods is shown on SAR images.