CENTER WEIGHTED MEDIAN FILTERS AND THEIR APPLICATIONS TO IMAGE-ENHANCEMENT

Abstract

The center weighted median (CWM) filter, which is a weighted median filter giving more weight only to the central value of each window, is studied. This filter can preserve image details while suppressing additive white and/or impulsive-type noise. The statistical properties of the CWM filter are analyzed. It is shown that the CWM filter can outperform the median filter. Some relationships between CWM and other median-type filters, such as the Winsorizing smoother and the multistage median filter, are derived. In an attempt to improve the performance of CWM filters, an adaptive CWM (ACWM) filter having a space varying central weight is proposed. We show that the ACWM filter is an excellent detail preserving smoother that can suppress signal-dependent noise as well as signal-independent noise.