DocumentCode
2031225
Title
Adaptive SFWO filter design
Author
Öten, Remzi ; de Figueiredo, Rui J.P.
Author_Institution
Lab. for Machine Intelligence, California Univ., Irvine, CA, USA
Volume
2
fYear
1998
fDate
4-7 Oct 1998
Firstpage
982
Abstract
In this paper we introduce a new design strategy for SFWO (sampled function weighted order) filters based on approximation theory. It is shown that with a good choice of noise tail-length estimator and a good approximation of the relation between this estimate and filter parameters, the adaptive SFWO filter gives very promising results when the noise type is unknown or varies with time. For this use, we also introduced a new tail-length estimator based on robust statistics
Keywords
adaptive filters; adaptive signal processing; approximation theory; digital filters; filtering theory; image restoration; network synthesis; noise; signal sampling; statistical analysis; adaptive SFWO filter design; approximation theory; filter parameters; image restoration; noise tail-length estimator; robust statistics; sampled function weighted order filters; Adaptive filters; Computer vision; Filtering theory; Laboratories; Laplace equations; Machine intelligence; Maximum likelihood estimation; Noise robustness; Parameter estimation; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location
Chicago, IL
Print_ISBN
0-8186-8821-1
Type
conf
DOI
10.1109/ICIP.1998.723719
Filename
723719
Link To Document