@inproceedings{e604d97787614933904b34e0d080e887,
title = "Nonparametric image interpolation and dictionary learning using spatially-dependent dirichlet and beta process priors",
abstract = "We present a Bayesian model for image interpolation and dictionary learning that uses two nonparametric priors for sparse signal representations: the beta process and the Dirichlet process. Additionally, the model uses spatial information within the image to encourage sharing of information within image subregions. We derive a hybrid MAP/Gibbs sampler, which performs Gibbs sampling for the latent indicator variables and MAP estimation for all other parameters. We present experimental results, where we show an improvement over other state-of-the-art algorithms in the low-measurement regime.",
keywords = "Bayesian models, Beta process, Dictionary learning, Dirichlet process, Image interpolation",
author = "John Paisley and Mingyuan Zhou and Guillermo Sapiro and Lawrence Carin",
year = "2010",
doi = "10.1109/ICIP.2010.5653350",
language = "English (US)",
isbn = "9781424479948",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "1869--1872",
booktitle = "2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings",
note = "2010 17th IEEE International Conference on Image Processing, ICIP 2010 ; Conference date: 26-09-2010 Through 29-09-2010",
}