Context-based graphical modeling for wavelet domain signal processing

Nilanjan Dasgupta, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Wavelet-domain hidden Markov tree (HMT) modeling provides a powerful approach to capture the underlying statistics of the wavelet coefficients. We develop a mutual information-based information-theoretic approach to quantify the interactions between the wavelet coefficients within a wavelet tree. This graphical method enables the design of a context-specific hidden Markov tree (HMT) by adding or deleting links from the traditional tree structure. The performance of the model is demonstrated on segmenting two-dimensional synthetic textures having intricate substructures, although the method can be used for signals of arbitrary dimensions.
Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages485-488
Number of pages4
StatePublished - Sep 25 2003
Externally publishedYes

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