Fast local polynomial regression approach for speckle noise removal
Walid K. Sharabati, Bowei Xi · 2016
In this paper we focus on speckle noise removal. Previously, variational models have been proposed to remove the multiplicative speckle noise. In general, the variational models require a significant amount of run time to converge, and need to set the proper tuning parameter values to achieve optimal noise reduction results. In this paper, we present a local polynomial regression model for speckle noise removal. Our regression model is fast, does not need to be trained on a set of images, does not rely on tuning parameters, and is capable of performing fast speckle noise removal on high resolution images. We have conducted extensive experiments to evaluate our model performance. Our polynomial regression filter outperformed popular noise removal algorithms.