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. © 2009, Brazilian Statistical Association. All rights reserved.
CITATION STYLE
Bustos, O., Ojeda, S., & Vallejos, R. (2009). Spatial ARMA models and its applications to image filtering. Brazilian Journal of Probability and Statistics, 23(2), 141–165. https://doi.org/10.1214/08-BJPS019
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