Spatial ARMA models and its applications to image filtering

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...

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Bibliographic Details
Published in:Brazilian journal of probability and statistics 2009-12, Vol.23 (2), p.141-165
Main Authors: Bustos, Oscar, Ojeda, Silvia, Vallejos, Ronny
Format: Article
Language:English
Subjects:
Autoregressive models
Autoregressive moving average
Estimators
Illustration
Image filters
Modeling
Moving images
Parametric models
Spatial models
Statistical Image and Signal Processing
Time series models
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Summary: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.
ISSN:0103-0752
2317-6199
DOI:10.1214/08-BJPS019