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Proceedings Paper

Statistical design of stack filters
Author(s): Jaakko T. Astola; Pauli Kuosmanen
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Paper Abstract

Nonlinear signal processing elements are increasingly needed in current signal processing systems. Stack filters form a large class of nonlinear filters, which have found a range of applications, giving excellent results in the area of noise filtering. Naturally, the development of fast procedures for the optimization of stack filters is one of the major aims in the research in the field. In this paper we study optimization of stack filters with a simplified scenario: the ideal signal is constant and the noise distribution is known. The objective of the optimization method presented in this paper is to find the stack filter producing optimal noise attenuation and satisfying given constraints. The constraints may limit the search into a set of stack filters with some common statistical description or they may describe certain structures which must be preserved or deleted. The objective of this paper is to illustrate that design of nonlinear filters is possible while using suitable signal and noise models.

Paper Details

Date Published: 24 September 1998
PDF: 17 pages
Proc. SPIE 3457, Mathematical Modeling and Estimation Techniques in Computer Vision, (24 September 1998); doi: 10.1117/12.323434
Show Author Affiliations
Jaakko T. Astola, Tampere Univ. of Technology (Finland)
Pauli Kuosmanen, Tampere Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 3457:
Mathematical Modeling and Estimation Techniques in Computer Vision
Francoise J. Preteux; Jennifer L. Davidson; Edward R. Dougherty, Editor(s)

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