Frequentist and Bayesian inference for Gaussian-log-Gaussian wavelet trees and statistical signal processing applications

Publikation: Forskning - peer reviewTidsskriftartikel

Abstrakt

We introduce new estimation methods for a subclass of the Gaussian scale mixture models for wavelet trees by Wainwright, Simoncelli and Willsky that rely on modern results for composite likelihoods and approximate Bayesian inference. Our methodology is illustrated for denoising and edge detection problems in two-dimensional images.
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Detaljer

We introduce new estimation methods for a subclass of the Gaussian scale mixture models for wavelet trees by Wainwright, Simoncelli and Willsky that rely on modern results for composite likelihoods and approximate Bayesian inference. Our methodology is illustrated for denoising and edge detection problems in two-dimensional images.
OriginalsprogEngelsk
TidsskriftSTAT
Vol/bind6
Tidsskriftsnummer1
Sider (fra-til)248-256
Antal sider9
ISSN2049-1573
DOI
StatusUdgivet - 2017
PublikationsartForskning
Peer reviewJa
ID: 263227059