The smoothing problem is considered for a two dimensional (2D) Gaussian Markov field defined on a finite rectangular lattice under Gaussian additive noise. The Gaussian Markov field is assumed to be generated by a (known) local correlation linking each site with the eight sites surrounding it in the lattice. In a former paper it has been shown that for such field (and with a further assumption of homogeneity that we here relax) a 2D realisation can be built up. Such realisation result represents the basis for the present paper, where a 2D- recursive optimal-smoothing algorithm is derived. Even though based on the realisation result, the present paper is nevertheless self-contained.

Two Dimensional Recursive Optimal Smoothing of Gaussian Random Fields

Francesco Carravetta;
2011

Abstract

The smoothing problem is considered for a two dimensional (2D) Gaussian Markov field defined on a finite rectangular lattice under Gaussian additive noise. The Gaussian Markov field is assumed to be generated by a (known) local correlation linking each site with the eight sites surrounding it in the lattice. In a former paper it has been shown that for such field (and with a further assumption of homogeneity that we here relax) a 2D realisation can be built up. Such realisation result represents the basis for the present paper, where a 2D- recursive optimal-smoothing algorithm is derived. Even though based on the realisation result, the present paper is nevertheless self-contained.
2011
Istituto di Analisi dei Sistemi ed Informatica ''Antonio Ruberti'' - IASI
Markov fields
Smoothing
Stochastic Processes
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/224843
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