Multichannel permutation filters

Author

Basu, Samit K. ; Arce, Gonzalo R.

Author_Institution

Dept. of Electr. Eng., Delaware Univ., Newark, DE, USA

Volume

1

fYear

1995

fDate

23-26 Oct 1995

Firstpage

370

Abstract

Vector order statistic based filters designed to exploit the correlation between the channels of a multichannel signal offer improved performance over purely marginal processing. In this paper, the class of permutation filters are extended to handle multichannel signals. Permutation filters are well suited for image processing; they are robust, able to preserve details, and edges in image and video signals, and can also model complicated non-linear systems accurately. Multichannel permutation filters are based on the permutation of a set of sequential observations from a multidimensional process. There exists no unique method for the ranking of vectors, so we evaluate two ranking formulations that preserve characteristics useful in constructing estimators. Simulation results for a video restoration problem are presented

Keywords

correlation methods; filtering theory; image restoration; image sequences; nonlinear filters; video signal processing; color video sequence; image processing; multichannel permutation filters; multichannel signals; multidimensional process; sequential observations; vector order statistic based filters; vector ranking formulations; video restoration problem; video signals; Aggregates; Genetic mutations; Image restoration; Information filtering; Information filters; Nonlinear filters; Robustness; Signal processing; Signal restoration; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.529723

Filename

529723