An Efficient Switching Median Filter Based on Local Outlier Factor

Abstract

An effective algorithm for removing impulse noise from corrupted images is presented under the framework of switching median filtering. Firstly, noisy pixels are distinguished by Local Outlier Factor incorporating with Boundary Discriminative Noise Detection (LOFBDND). Then, the directional weighted median filter is adopted to remove the detected impulses by replacing each noisy pixel with the weighted mean of its neighbors in the filtering window. Our noise detection algorithm makes the decision so accurate that the miss detection rate and false detection rate are very low. Extensive simulation results show that our method provides better performance in terms of PSNR and MAE than many other median filters for impulse noise removal.