[ABE-L] Ciclo de Seminários do Departamento de Estatística – UFRN

['moizes silva' via abe-l@ime.usp.br]

Ciclo de Seminários do Departamento de Estatística – UFRN
Prezados, o Departamento de Estatística da Universidade Federal do Rio Grande do Norte - UFRN convida a todos para participar do seminário que será realizado hoje, 28/06, às 14h. Seguem informações abaixo

Link meet: https://meet.google.com/mtp-ekup-nur
Link YouTube: https://www.youtube.com/channel/UCr_8R_aiS69hroG4-Yvzv4Q
Palestrante: Prof. Dr. Fábio Mariano Bayer
Title: 2-D Rayleigh Autoregressive Moving Average Model for SAR Image Modeling
Abstract: Two-dimensional (2-D) autoregressive moving average (ARMA) models are commonly applied to describe real-world image data, usually assuming Gaussian or symmetric noise. However, real-world data often present non-Gaussian signals, with asymmetrical distributions and strictly positive values. In particular, SAR images are known to be well characterized by the Rayleigh distribution. In this context, this paper introduces an ARMA model tailored for 2-D Rayleigh-distributed data -- the 2-D RARMA model. The 2-D RARMA model is derived and conditional likelihood inferences are discussed. The proposed model was submitted to extensive Monte Carlo simulations to evaluate the performance of the conditional maximum likelihood estimators. Moreover, in the context of SAR image processing, two comprehensive numerical experiments were performed comparing anomaly detection and image modeling results of the proposed model with traditional 2-D ARMA models and competing methods in the literature.
This is a joint work with Bruna Gregory Palm and Renato J. Cintra.


Atenciosamente,Moizés da Silva Melo.
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