Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors

John Paisley, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin
2010 2010 IEEE International Conference on Image Processing  
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,
more » ... rimental results, where we show an improvement over other state-of-the-art algorithms in the low-measurement regime.
doi:10.1109/icip.2010.5653350 dblp:conf/icip/PaisleyZSC10 fatcat:tprbfg6o6rfcrphownybk7t5re