Statistics of stack filters with mirrored threshold decomposition

Author

Shmulevich, I. ; Paredes, J.L. ; Arce, G.R.

Author_Institution

Signal Process. Lab., Tampere Univ. of Technol., Finland

Volume

6

fYear

2000

fDate

2000

Firstpage

3826

Abstract

The output distribution formula for stack filters based on mirrored threshold decomposition is derived. This formula allows one to compute the cumulative distribution function of the output of a stack filter for a given input noise distribution. Mirrored threshold decomposition permits us to analyze the input-output characteristics of the stack filter in the binary domain. The sliding window operation of the stack filter is modeled by a deterministic finite automaton. The output distribution of the filter is obtained by interpreting the automaton as a Markov Chain whose transition probabilities depend on the probabilistic description of the binary input signal

Keywords

Markov processes; filtering theory; finite automata; noise; probability; stack filters; statistical analysis; Markov Chain; binary input signal; cumulative distribution function; deterministic finite automaton; image processing; input noise distribution; input-output characteristics; mirrored threshold decomposition; nonlinear filters; output distribution formula; probabilistic description; rank selection probabilities; signal processing; sliding window operation; stack filters; stack smoothers; statistical optimization; statistics; transition probabilities; Automata; Band pass filters; Distributed computing; Filtering; Low pass filters; Nonlinear filters; Signal processing; Statistical analysis; Statistical distributions; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1520-6149

Print_ISBN

0-7803-6293-4

Type

conf

DOI

10.1109/ICASSP.2000.860237

Filename

860237