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Models of Conariance Functions of Gaussian Random Fields Escaping from Isotopy, Stationarity and Non-Negativity

Lookup NU author(s): Professor Emilio Porcu

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Abstract

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.

Publication metadata

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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