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Hidden Markov Tree Modeling of Complex Wavelet Transforms
Multiresolution signal and image models such as the hidden Markov tree aim to capture the statistical structure of smooth and singular (edgy) regions. Unfortunately, models based on the orthogonal wavelet transform suffer ...
Multiscale Classification using Complex Wavelets and Hidden Markov Tree Models
Multiresolution signal and image models such as the hidden Markov tree (HMT) aim to capture the statistical structure of smooth and singular (textured and edgy) regions. Unfortunately, models based on the orthogonalwavelet ...
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 ...
Multiscale SAR Image Segmentation using Wavelet-domain Hidden Markov Tree Models
We study the segmentation of SAR imagery using wavelet-domain Hidden Markov Tree (HMT) models. The HMT model is a tree-structured probabilistic graph that captures the statistical properties of the wavelet transforms of ...