Now showing items 1-6 of 6
Estimation-Quantization Geometry Coding Using Normal Meshes
We propose a new algorithm for compressing three-dimensional triangular mesh data used for representing surfaces. We apply the Estimation-Quantization (EQ) algorithm originally designed for still image compression to the ...
Multiscale Image Segmentation Using Joint Texture and Shape Analysis
We develop a general framework to simultaneously exploit texture and shape characterization in multiscale image segmentation. By posing multiscale segmentation as a model selection problem, we invoke the powerful framework ...
Wavelet-based deconvolution for ill-conditioned systems
We propose a hybrid approach to wavelet-based deconvolution that comprises Fourier-domain system inversion followed by wavelet-domain noise suppression. In contrast to other wavelet-based deconvolution approaches, the ...
Hidden Markov Tree Models for Complex Wavelet Transforms
Multiresolution models such as the hidden Markov tree (HMT) aim to capture the statistical structure of signals and images by leveraging two key wavelet transform properties: wavelet coefficients representing smooth/singular ...
ForWaRD: Fourier-Wavelet Regularized Deconvolution for Ill-Conditioned Systems
We propose an efficient, hybrid <i>Fourier-Wavelet Regularized Deconvolution</i> (ForWaRD) algorithm that performs noise regularization via scalar shrinkage in both the Fourier and wavelet domains. The Fourier shrinkage ...
Bayesian Tree-Structured Image Modeling using Wavelet-domain Hidden Markov Models
Wavelet-domain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint probability density of the wavelet ...