Weighted Iterative Truncated Mean Filter

• Published in: IEEE transactions on signal processing Vol. 61; no. 16; pp. 4149 - 4160
• Main Authors: Miao, Zhenwei, Jiang, Xudong
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 15.08.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; band-pass filter; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; high-pass filter; Information, signal and communications theory; ITM filter; noise suppression; nonlinear filter; Signal and communications theory; Signal, noise; Telecommunications and information theory; weighted median filter; Performance evaluation; Weighting filter; noise suppression; Noise reduction; nonlinear filter; ITM filter; Non linear filter; Iterative method; band-pass filter; High pass filter; Stopping rule; high-pass filter; Signal processing; weighted median filter; Band pass filter; Median filter
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2013.2267739

The iterative truncated arithmetic mean (ITM) filter was proposed recently. It offers a way to estimate the sample median by simple arithmetic computing instead of the time consuming data sorting. In this paper, a rich class of filters named weighted ITM (WITM) filters are proposed. By iteratively truncating the extreme samples, the output of the WITM filter converges to the weighted median. Proper stopping criterion makes the WITM filters own merits of both the weighted mean and median filters and hence outperforms the both in some applications. Three structures are designed to enable the WITM filters being low-, band- and high-pass filters. Properties of these filters are presented and analyzed. Experimental evaluations are carried out on both synthesis and real data to verify some properties of the WITM filters.