An adaptive median filter algorithm based on B-spline function

According to the B-spline convolution mask, first, the contrast sensitiveness (CS) is computed and then is viewed as a noise sensitiveness coefficient (NSC) to adaptively determine a noise-recognized threshold value. Based on the noise density function (NDF) in a 3×3 window, the filtering window size is adaptively adjusted, and then a median filter is used to eliminate the noise-marked pixels. The experiment results show that the proposed algorithm can preserve image detail information well and effectively remove the noises, particularly the impulse noises that is also called salt-and-pepper noises superimposed on the computed tomography (CT) and magnetic resonance imaging (MRI) medical images. © 2011 Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.