Morphological filtering and convolution

This paper presents a new class of nonlinear filtering for 1D and 2D periodic signals buried in noise. Morphological filters are convolved with proper transfer function. The resulted filter, called convolved morphological filter, shows better performance both in time and frequency domain, compared w...

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Bibliographische Detailangaben
Hauptverfasser:	Sedaaghi, M.H, Wu, Q.H
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Applied sciences Detection, estimation, filtering, equalization, prediction Exact sciences and technology Filtering methods in signal processing Image recognition Information, signal and communications theory Optical, image and video signal processing Signal and communications theory Signal processing theory Signal, noise Telecommunications and information theory
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	This paper presents a new class of nonlinear filtering for 1D and 2D periodic signals buried in noise. Morphological filters are convolved with proper transfer function. The resulted filter, called convolved morphological filter, shows better performance both in time and frequency domain, compared with the performance of individually applied MF and convolution.
ISSN:	0537-9989
DOI:	10.1049/cp:19980233