# Order selection of 2-D AR model using a lattice representation and information criteria for texture analysis

Signal Processing , Volume 3, pages 1823-1826, Proc. EUSIPCO 2000, Tampere, Finlande - September 2000

In the context of parametric modeling for image processing, we use a lattice representation, i.e. based on reflection coefficients, to derive an estimation method for both the parameters and the order of the 2-D Quarter Plane Autoregressive model. The method is based on the combination of an Information Criterion (IC) and the prediction errors of models computed from a lattice parameter estimation algorithm. In this paper, we propose the use of two criteria which are consistent conversely the Akaike one: the Kashyap and Chelappa criterion is a 2-D extension of Bayesian Information Criterion (BIC); the second criteria, called jb criterion, which is extended here to the 2-D case, is a generalization drawn on Rissanen's works. Simulations are provided on synthetic and natural textures. The results show the interest of using lattice estimation algorithm and jb criterion to a characterization of textures.

## BibTex references

@InProceedings{AO2000_2443,

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author | = {Alata, O. and Olivier, C.}, | |

title | = {Order selection of 2-D AR model using a lattice representation and information criteria for texture analysis.}, | |

booktitle | = {Signal Processing }, | |

series | = {10}, | |

volume | = {3}, | |

pages | = {1823-1826}, | |

month | = {September}, | |

year | = {2000}, | |

note | = {Proc. EUSIPCO 2000, Tampere, Finlande}, |