We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
Wavelet-domain hidden Markov models (HMMs) have been recently proposed and applied to image processing, e.g., image denoising. In this paper, we develop a new HMM, called local co...
The Extended Baum-Welch (EBW) Transformations is one of a variety of techniques to estimate parameters of Gaussian mixture models. In this paper, we provide a theoretical framewor...
Dimitri Kanevsky, Tara N. Sainath, Bhuvana Ramabha...
Abstract— Ultra-wideband (UWB) communications is envisaged to be deployed in indoor environments, where the noise distribution is decidedly non-Gaussian. A critical challenge for...
To track objects in video sequences, many studies have been done to characterize the target with respect to its color distribution. Most often, the Gaussian Mixture Model (GMM) is ...