Frequentist and Bayesian inference for Gaussian-log-Gaussian wavelet trees, and statistical signal processing applications
Statistics Theory
2017-08-14 v4 Methodology
Statistics Theory
Abstract
We introduce new estimation methods for a sub-class of the Gaussian scale mixture models for wavelet trees by Wainwright, Simoncelli & 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.
Cite
@article{arxiv.1405.0379,
title = {Frequentist and Bayesian inference for Gaussian-log-Gaussian wavelet trees, and statistical signal processing applications},
author = {Robert Dahl Jacobsen and Jesper Møller},
journal= {arXiv preprint arXiv:1405.0379},
year = {2017}
}