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Title: On the optimality of a new class of 2D recursive filters (English)
Author: Jetto, Leopoldo
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 35
Issue: 6
Year: 1999
Pages: [777]-792
Summary lang: English
Category: math
Summary: The purpose of this paper is to prove the minimum variance property of a new class of 2D, recursive, finite-dimensional filters. The filtering algorithms are derived from general basic assumptions underlying the stochastic modelling of an image as a 2D gaussian random field. An appealing feature of the proposed algorithms is that the image pixels are estimated one at a time; this makes it possible to save computation time and memory requirement with respect to the filtering procedures based on strip processing. Experimental results show the effectiveness of the new filtering schemes. (English)
Keyword: minimum variance property
Keyword: finite-dimensional filter
Keyword: Gaussian random field
Keyword: 2D recursive filters
Keyword: strip processing
Keyword: image pixels
MSC: 93C30
MSC: 93E11
MSC: 94A08
idZBL: Zbl 1274.93261
idMR: MR1747976
Date available: 2009-09-24T19:30:04Z
Last updated: 2015-03-27
Stable URL:
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