Sciweavers

Share
ICIP
2007
IEEE

Image Denoising with Nonparametric Hidden Markov Trees

9 years 10 months ago
Image Denoising with Nonparametric Hidden Markov Trees
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients are marginally distributed according to infinite, Dirichlet process mixtures. A hidden Markov tree is then used to couple the mixture assignments at neighboring nodes. Via a Monte Carlo learning algorithm, the resulting hierarchical Dirichlet process hidden Markov tree (HDP-HMT) model automatically adapts to the complexity of different images and wavelet bases. Image denoising results demonstrate the effectiveness of this learning process.
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord
Added 21 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2007
Where ICIP
Authors Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jordan
Comments (0)
books