Some convergence properties of median filters

A median filter is a nonlinear digital filter which consists of a window of length 2N + 1 that moves over a signal of finite length. For each input sample, the corresponding output point is the median of all samples in the window centered on that input sample. Any finite length, M -level, signal that ends with constant regions of length N + 1 will converge to an invariant signal in a finite number of passes of this median filter. Such an invariant signal is called a root. The concept of a root signal has proved to be crucial in understanding the properties of the median filter, root signals are to median filters what passband signals are to linear signals. In this paper, two results concerning the rate at which a signal is filtered to a root are developed. For a window of width 3, we derive a recursive formula to count the number of binary signals of length L that converge to a root in exactly m passes of a median filter. Also, we show that, given a window of width 2N + 1 , any signal of length L will converge to a root in at most 3\lceil\frac{(L-2)}{2(N + 2)}\rceil passes of the filter.

[1]  V. Benes Exact finite-dimensional filters for certain diffusions with nonlinear drift , 1981 .

[2]  Edward J. Coyle,et al.  Root properties and convergence rates of median filters , 1985, IEEE Trans. Acoust. Speech Signal Process..

[3]  E. J. Coyle On the optimality of rank order operations , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  John W. Tukey,et al.  Nonlinear (nonsuperposable) methods for smoothing data , 1974 .

[5]  Edward J. Coyle,et al.  Stack filters , 1986, IEEE Trans. Acoust. Speech Signal Process..

[6]  Gonzalo R. Arce,et al.  BTC Image Coding Using Median Filter Roots , 1983, IEEE Trans. Commun..

[7]  Lawrence R. Rabiner,et al.  Applications of a nonlinear smoothing algorithm to speech processing , 1975 .

[8]  N. Gallagher,et al.  An application of median filters to digital television , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Thomas Kailath,et al.  Nonlinear filtering with counting observations , 1975, IEEE Trans. Inf. Theory.

[10]  G. Wise,et al.  A theoretical analysis of the properties of median filters , 1981 .

[11]  Edward J. Coyle,et al.  Threshold decomposition of multidimensional ranked order operations , 1985 .

[12]  Edward J. Coyle,et al.  Analysis and Implementation of Median Type Filters , 1984 .

[13]  J. Fitch,et al.  The analog median filter , 1986 .

[14]  T. Nodes,et al.  Median filters: Some modifications and their properties , 1982 .

[15]  Allan L. Fisher Systolic Algorithms for Running Order Statistics in Signal and Image Processing , 1981 .

[16]  G. Neudeck,et al.  VLSI Implementation of a fast rank order filtering algorithm , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[17]  J. Doob Stochastic processes , 1953 .

[18]  G. Arce,et al.  State description for the root-signal set of median filters , 1982 .

[19]  J. Fitch,et al.  Median filtering by threshold decomposition , 1984 .

[20]  N. Gallagher,et al.  Two-dimensional root structures and convergence properties of the separable median filter , 1983 .

[21]  Thomas S. Huang,et al.  Image restoration using order-constrained least-squares methods , 1983, ICASSP.