Robust Estimation for Two-Dimensional Autoregressive Processes Based on Bounded Innovation Propagation Representations

Autor: Britos, Grisel Maribel, Ojeda, Silvia María

Robust methods have been a successful approach to deal with contaminations and noises in image processing. In this paper, we introduce a new robust method for two-dimensional autoregressive models. Our method, called BMM-2D, relies on representing a

Externí odkaz: http://arxiv.org/abs/1807.02602

Asymptotic properties of BMM-estimator in bidimensional autoregressive processes

Autor: Britos, Grisel M., Ojeda, Silvia M., Rodríguez Astrain, Laura A., Bustos, Oscar H.

Publikováno v: In Journal of Statistical Planning and Inference December 2020 209:208-228

Estimación Robusta en Modelos ARMA Bidimensionales. Aplicación al procesamiento de imágenes digitales

Autor: Britos, Grisel Maribel

Publikováno v: Repositorio Digital Universitario (UNC)
Universidad Nacional de Córdoba
instacron:UNC
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET

Este trabajo se focalizó en el problema de la estimación robusta de los parámetros en modelos autorregresivos bidimensionales con contaminación. Se propone un nuevo método de estimación robusta de los parámetros de estos modelos, denominado BM

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::04a586a57f9fc5f5066f69d33dc601c7

Robust estimation for spatial autoregressive processes based on bounded innovation propagation representations.

Autor: Britos, Grisel Maribel, Ojeda, Silvia María

Publikováno v: Computational Statistics; Sep2019, Vol. 34 Issue 3, p1315-1335, 21p

An image quality index based on coefficients of spatial association with an application to image fusion

Autor: Silvia Ojeda, Grisel Maribel Britos, Ronny Vallejos

Publikováno v: CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET

In the last decade, image quality indices have received considerable attention to quantify the dissimilarity between two images. The codispersion coefficient, commonly used in spatial statistics to address the association between two processes has al

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36fc8c71148fb3df2f11947aee7a951e
https://www.sciencedirect.com/science/article/pii/S2211675317301975