Brazilian Journal of Probability and Statistics

Spatial ARMA models and its applications to image filtering

Oscar Bustos, Silvia Ojeda, and Ronny Vallejos

Source: Braz. J. Probab. Stat. Volume 23, Number 2 (2009), 141-165.

Abstract

The objective of this review paper is to summarize the main properties of the spatial ARMA models and describe some of the well-known methods used in image filtering based on estimation of spatial autoregressive models. A new proposal based on robust RA estimation is also presented. Previous studies have shown that under additive outliers the RA estimator is resistant to a small percentage of contamination and behaves better than the LS, M, and GM estimators. A discussion about how well these models fit to a digital image is presented. Some applications using real images are presented to illustrate how an image is filtered in practice.

Keywords: Spatial autoregressive model; robust estimators; image filtering algorithm

Full-text: Access denied (no subscription detected)

We're sorry, but we are unable to provide you with the full text of this article because we are not able to identify you as a subscriber.
If you have a personal subscription to this journal, then please login. If you are already logged in, then you may need to update your profile to register your subscription. Read more about accessing full-text
Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.bjps/1256562755
Digital Object Identifier: doi:10.1214/08-BJPS019

References

Allende, H. and Heiller, S. (1992). Recursive generalized M estimates for autoregressive moving-average models., Journal of Time Series Analysis 13 1–18.
Mathematical Reviews (MathSciNet): MR1149267
Zentralblatt MATH: 0850.62666
Digital Object Identifier: doi:10.1111/j.1467-9892.1992.tb00091.x
Allende, H., Galbiati, J. and Vallejos, R. (1998). Digital image restoration using autoregressive time series type models., Bulletin European Spatial Agency 434 53–59.
Allende, H., Galbiati, J. and Vallejos, R. (2001). Robust image modeling on image processing., Pattern Recognition Letters 22 1219–1231.
Banerjee, S., Carlin, B. and Gelfand, A. (2004)., Hierarchical Modeling and Analysis for Spatial Data. Chapman and Hall/CRC Press, Florida.
Zentralblatt MATH: 1053.62105
Banham, M. R. and Katsaggelos, A. K. (1997). Digital image restoration., IEEE Signal Processing Magazine 14 24–41.
Basu, S. and Reinsel, G. (1993). Properties of the spatial unilateral first-order ARMA model., Advances in Applied Probbability 25 631–648.
Mathematical Reviews (MathSciNet): MR1234300
Zentralblatt MATH: 0780.62072
Digital Object Identifier: doi:10.2307/1427527
Bennet, J. and Khotanzad, A. (1999). Maximum likelihood estimation methods for multispectral random field image models., IEEE Transaction Pattern Analysis and Machine Intelligence 21 537–543.
Besag, J. (1974). Spatial interaction and the statistical analysis of lattice systems (with discussion)., Journal of the Royal Statistical Society, Series B 55 192–236.
Mathematical Reviews (MathSciNet): MR373208
Bustos, O. and Yohai, V. (1986). Robust estimates for ARMA models., Journal of the American Statistical Association 81 55–68.
Mathematical Reviews (MathSciNet): MR830576
Digital Object Identifier: doi:10.2307/2287983
Bustos, O., Ruiz, M., Ojeda, S., Vallejos, R. and Frery, A. (2008). Asymptotic behavior of RA- estimates in autoregressive processes., Submitted.
Chang, I., Tiao, G. C. and Chen, C. (1988). Estimation of time series parameters in the presence of outliers., Technometrics 3 193–204.
Mathematical Reviews (MathSciNet): MR943602
Digital Object Identifier: doi:10.2307/1270165
Chen, C. and Lui, L. (1993). Joint estimation of model parameters and outliers in time series., Journal of the American Statistical Association 88 284–297.
Cliff, A. and Ord, J. (1981)., Spatial Processes: Models and Applications. Pion Ltd., London.
Mathematical Reviews (MathSciNet): MR632256
Cullis, B. R. and Glesson, A. C. (1991). Spatial analysis of field experiments—an extension to two dimensions., Biometrics 47 1449–1460.
Eunho, H. and Newton, H. J. (1993). The bias of estimators of causal spatial autoregressive models., Biometrika 80 242–245.
Francos, J., Narasimhan, A. and Woods, J. W. (1995). Maximum likelihood parameter estimation of textures using a Wold-decomposition based model., IEEE Transactions on Image Processing 4 1655–1666.
Francos, J. and Friedlander, B. (1998). Parameter estimation of two-dimensional moving average random fields., IEEE Transaction Signal Processing 46 2157–2165.
Mathematical Reviews (MathSciNet): MR1667322
Zentralblatt MATH: 0978.60053
Digital Object Identifier: doi:10.1109/78.705427
Francos, J. and Nehorai, A. (2003). Interference mitigation in STAP using the two-dimensional Wold decomposition model., IEEE Transactions on Signal Processing 51 2461–2470.
Fox, A. J. (1972). Outliers in time series., Journal of the Royal Statistical Society, Series B 34 350–363.
Mathematical Reviews (MathSciNet): MR331681
Griffith, D. A. (1988)., Advanced Spatial Statistics. Kluver, Dordrecht, The Netherlands.
Grondona, M. R., Crossa, J., Fox, P. N. and Pfeiffer, W. H. (1996). Analysis of variety yield trials using two-dimensional separable ARIMA processes., Biometrics 52 763–770.
Guyon, X. (1995)., Random Fields on a Network. Modeling, Statistics and Applications. Springer, Berlin.
Mathematical Reviews (MathSciNet): MR1344683
Zentralblatt MATH: 0839.60003
Haining, R. P. (1978). The moving average model for spatial interaction., Transactions and Papers, Institute of British Geographers, New Series 3 202–225.
Isaksson, A. J. (1993). Analysis of identified 2-D noncausal models., IEEE Transactions on Information Theory 39 525–534.
Jain, A. K. (1989)., Fundamentals of Digital Image Processing. Prentice Hall, Lugar.
Zentralblatt MATH: 0744.68134
Kashyap, R. L. and Chellappa, R. (1983). Estimation and choice of neighboors in spatial-interaction models of images., IEEE Transactions on Information Theory 19 60–72.
Kashyap, R. and Eom, K. (1988). Robust images techniques with an image restoration application., IEEE Transactions on Acoustics and Speech Signal Processing 36 1313–1325.
Katsaggelos, A. K. (1989). Iterative image restoration algorithms., Optical Engineering 28 735–748.
Krishnamurthy, R., Woods, J. and Francos, J. (1996). Adaptive restoration of textures images with mixed spectra using a generalized Wiener filter., IEEE Transactions on Image Processing 5 648–652.
Kokaram, A. (2004). A statistical framework for picture reconstruction using 2D AR models., Image and Vision Computing 22 165–171.
Liu, F. and Piccard, R. (1996). Periodicity, directionality and randomness: Wold features for image modeling and retrieval., IEEE Transactions on Pattern Analysis and Machine Intelligence 18 722–733.
Martin, R. J. (1979). A subclass of lattice processes applied to a problem in planar sampling., Biometrika 66 209–217.
Mathematical Reviews (MathSciNet): MR548186
Zentralblatt MATH: 0404.62017
Digital Object Identifier: doi:10.1093/biomet/66.2.209
Martin, R. D. (1980). Robust estimation of autoregressive models. In, Direction in Time Series (D. R. Brillinger and G. C. Tiao, eds.). Institute of Mathematical Statistics, Haywood, CA.
Mathematical Reviews (MathSciNet): MR624655
Zentralblatt MATH: 0531.62038
Martin, R. J. (1990). The use of time-series models and methods in the analysis of agricultural field trials., Communications in Statistics Theory Methods 19 55–81.
Mathematical Reviews (MathSciNet): MR1060398
Digital Object Identifier: doi:10.1080/03610929008830187
Martin, R. J. (1996). Some results on unilateral ARMA lattice processes., Journal of Statistical Planning and Inference 50 395–411.
Mathematical Reviews (MathSciNet): MR1394140
Zentralblatt MATH: 0848.62051
Digital Object Identifier: doi:10.1016/0378-3758(95)00066-6
Ojeda, S. M. (1999). Robust RA estimators for bidimensional autoregressive models. Ph.D. dissertation, Facultad de Matemáticas, Astronomía y Física, Universidad Nacional de Córdoba, Argentina.
Ojeda, S. M., Vallejos, R. O. and Lucini, M. (2002). Performance of RA estimator for bidimensional autoregressive models., Journal of Statistical Simulation and Computation 72 47–62.
Mathematical Reviews (MathSciNet): MR1907809
Zentralblatt MATH: 1091.62536
Digital Object Identifier: doi:10.1080/00949650211426
Quenouille, M. H. (1949). Problems in plane sampling., Annals of Mathematical Statistics 20 355–375.
Mathematical Reviews (MathSciNet): MR32175
Digital Object Identifier: doi:10.1214/aoms/1177729989
Project Euclid: euclid.aoms/1177729989
Rukhin, A. and Vallejos, R. (2008). Codispersion coefficient for spatial and temporal series., Statistics and Probability Letters 78 1290–1300.
Mathematical Reviews (MathSciNet): MR2444319
Tsay, R. S., Peña, D. and Pankratz, A. E. (2000). Outliers in multivariate time series., Biometrics 87 789–804.
Tsay, R. S. (1988). Outliers, level shifts, and variance change in time series., Journal of Forecasting 7 1–20.
Tjostheim, D. (1978). Statistical spatial series modelling., Advances in Applied Probability 10 130–154.
Mathematical Reviews (MathSciNet): MR471224
Digital Object Identifier: doi:10.2307/1426722
Vallejos, R. and Mardesic, T. (2004). A recursive algorithm to restore images based on robust estimation of NSHP autoregressive models., Journal of Computational and Graphical Statistics 13 674–682.
Mathematical Reviews (MathSciNet): MR2087721
Digital Object Identifier: doi:10.1198/106186004X2183
Vallejos, R. and Garcia-Donato, G. (2006). Bayesian analysis of contaminated quarter plane moving average models., Journal of Statistical Computation and Simulation 76 131–147.
Mathematical Reviews (MathSciNet): MR2199883
Zentralblatt MATH: 1088.62043
Digital Object Identifier: doi:10.1080/00949650412331321133
Vallejos, R., Ojeda, S. and Bustos, O. (2008). On RA and GM estimates for spatial autoregressive models., Submitted.
Whittle, P. (1954). On stationary processes on the plane., Biometrika 41 434–449.
Mathematical Reviews (MathSciNet): MR67450
Zentralblatt MATH: 0058.35601

2009 © Brazilian Statistical Association