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

摘要

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.