Parameter estimation of two-dimensional moving average random fields

Joseph M. Francos, Benjamin Friedlander

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


his paper considers the problem of estimating the parameters of two-dimensional (2-D) moving average random (MA) fields. We first address the problem of expressing the covariance matrix of nonsymmetrical half-plane, noncausal, and quarter-plane MA random fields in terms of the model parameters. Assuming the random field is Gaussian, we derive a closedform expression for the Cramér-Rao lower bound (CRLB) on the error variance in jointly estimating the model parameters. A computationally efficient algorithm for estimating the parameters of the MA model is developed. The algorithm initially fits a 2-D autoregressive model to the observed field and then uses the estimated parameters to compute the MA model. A maximumlikelihood algorithm for estimating the MA model parameters is also presented. The performance of the proposed algorithms is illustrated by Monte-Carlo simulations and is compared with the Cramér-Rao bound.

Original languageEnglish
Pages (from-to)2157-2165
Number of pages9
JournalIEEE Transactions on Signal Processing
Issue number8
StatePublished - 1 Dec 1998


  • Maximum likelihood
  • Moving average random fields
  • Parameter estimation
  • Random fields

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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