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Lookup NU author(s): Professor Emilio Porcu
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This paper represents a survey of recent advances in modeling of space or space-time Gaussian Random Fields(GRF), tools of Geostatistics at hand for the understanding of special cases of noise in image analysis. They canbe used when stationarity or isotropy are unrealistic assumptions, or even when negative covariance betweensome couples of locations are evident. We show some strategies in order to escape from these restrictions, onthe basis of rich classes of well known stationary or isotropic non negative covariance models, and throughsuitable operations, like linear combinations, generalized means, or with particular Fourier transforms.
Author(s): Gregori P, Porcu E, Mateu J
Publication type: Article
Publication status: Published
Journal: Image Analysis & Stereology
Year: 2014
Volume: 33
Issue: 1
Pages: 75-81
Online publication date: 01/03/2014
Acceptance date: 18/01/2014
ISSN (print): 1580-3139
ISSN (electronic): 1854-5165
Publisher: International Society for Stereology
URL: https://doi.org/10.5566/ias.v33.p75-81
DOI: 10.5566/ias.v33.p75-81
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