Bounds on the accuracy of estimating the parameters of discrete homogeneous random fields with mixed spectral distributions

This paper considers the achievable accuracy in jointly estimating the parameters of a real-valued two-dimensional (2-D) homogeneous random field with mixed spectral distribution, from a single observed realization of it. On the basis of a 2-D Wold-like decomposition, the field is represented as a sum of mutually orthogonal components of three types: purely indeterministic, harmonic, and evanescent. An exact form of the Cramer-Rao lower bound on the error variance in jointly estimating the parameters of the different components is derived. It is shown that the estimation of the harmonic component is decoupled from that of the purely indeterministic and the evanescent components. Moreover, the bound on the parameters of the purely indeterministic and the evanescent components is independent of the harmonic component. Numerical evaluation of the bounds provides some insight into the effects of various parameters on the achievable estimation accuracy.

[1]  Joseph M. Francos,et al.  Parameter estimation of two-dimensional moving average random fields , 1998, IEEE Trans. Signal Process..

[2]  Xianda Zhang Two-dimensional harmonic retrieval and its time-domain analysis technique , 1991, IEEE Trans. Inf. Theory.

[3]  Basilis Gidas,et al.  Parameter Estimation for Gibbs Distributions from Partially Observed Data , 1992 .

[4]  Yingbo Hua,et al.  Statistical analysis of an eigendecomposition based method for 2-D frequency estimation , 1994, Autom..

[5]  A. M. Walker On the estimation of a harmonic component in a time series with stationary independent residuals , 1971 .

[6]  T. Marzetta Two-dimensional linear prediction: Autocorrelation arrays, minimum-phase prediction error filters, and reflection coefficient arrays , 1980 .

[7]  Rama Chellappa,et al.  Two-dimensional robust spectrum estimation , 1988, IEEE Trans. Acoust. Speech Signal Process..

[8]  Alf J. Isaksson,et al.  Analysis of identified 2-D noncausal models , 1993, IEEE Trans. Inf. Theory.

[9]  N. Balram,et al.  Noncausal Gauss Markov random fields: Parameter structure and estimation , 1993, IEEE Trans. Inf. Theory.

[10]  M. Morf,et al.  Inverses of Toeplitz operators, innovations, and orthogonal polynomials , 1975, 1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes.

[11]  T.F. Quatieri,et al.  Statistical model-based algorithms for image analysis , 1986, Proceedings of the IEEE.

[12]  M. Priestley The analysis of two-dimensional stationary processes with discontinuous spectrat , 1964 .

[13]  John W. Woods,et al.  Maximum-likelihood parameter estimation of the harmonic, evanescent, and purely indeterministic components of discrete homogeneous random fields , 1993, IEEE Trans. Inf. Theory.

[14]  A. H. Kayran,et al.  Lattice parameter autoregressive modeling of two-dimensional fields--Part I: The quarter-plane case , 1984 .

[15]  Rangasami L. Kashyap,et al.  Characterization and estimation of two-dimensional ARMA models , 1984, IEEE Trans. Inf. Theory.

[16]  Joseph M. Francos,et al.  A unified texture model based on a 2-D Wold-like decomposition , 1993, IEEE Trans. Signal Process..

[17]  P. Whittle ON STATIONARY PROCESSES IN THE PLANE , 1954 .

[18]  Calyampudi Radhakrishna Rao,et al.  Linear Statistical Inference and its Applications , 1967 .

[19]  James H. McClellan,et al.  The extension of Pisarenko's method to multiple dimensions , 1982, ICASSP.

[20]  John W. Woods,et al.  Two-dimensional discrete Markovian fields , 1972, IEEE Trans. Inf. Theory.

[21]  D. B. Preston Spectral Analysis and Time Series , 1983 .

[22]  Bin Zhou,et al.  Maximum likelihood estimation of 2-D superimposed exponential signals , 1994, IEEE Trans. Signal Process..

[23]  Yingbo Hua Estimating two-dimensional frequencies by matrix enhancement and matrix pencil , 1992, IEEE Trans. Signal Process..

[24]  J. M. Francos,et al.  A Wold-Like Decomposition of Two-Dimensional Discrete Homogeneous Random Fields , 1995 .

[25]  J. M. Francos,et al.  A Wold-Like Decomposition of 2-D Discrete Homogeneous Random Fields , 1995 .

[26]  J. M. Francos,et al.  Maximum likelihood parameter estimation of textures using a wold-decomposition based model , 1995, IEEE Transactions on Image Processing.

[27]  H. Derin,et al.  Discrete-index Markov-type random processes , 1989, Proc. IEEE.

[28]  John W. Woods,et al.  Maximum-likelihood parameter estimation of discrete homogeneous random fields with mixed spectral distributions , 1996, IEEE Trans. Signal Process..

[29]  Yingbo Hua,et al.  Estimating two-dimensional frequencies by matrix enhancement and matrix pencil , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[30]  R. Kumaresan,et al.  A two-dimensional technique for frequency-wavenumber estimation , 1981, Proceedings of the IEEE.

[31]  A.K. Jain,et al.  Advances in mathematical models for image processing , 1981, Proceedings of the IEEE.

[32]  Benjamin Friedlander,et al.  Computation of the exact information matrix of Gaussian time series with stationary random components , 1985, 1985 24th IEEE Conference on Decision and Control.