Spatial ARMA models and its applications to image filtering

被引：28

作者：

Bustos, Oscar ^{[1
]}

Ojeda, Silvia ^{[1
]}

Vallejos, Ronny ^{[2
,3
]}

机构：

[1] Univ Nacl Cordoba, Fac Matemat Astron & Fis, RA-5000 Cordoba, Argentina

[2] Univ Tecn Federico Santa Maria, Dept Matemat, Valparaiso, Chile

[3] Univ Valparaiso, Valparaiso, Chile

来源：

BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS | 2009年 / 23卷 / 02期

关键词：

Spatial autoregressive model; robust estimators; image filtering algorithm; PARAMETER-ESTIMATION; RESTORATION; OUTLIERS;

D O I：

10.1214/08-BJPS019

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：141 / 165

页数：25

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