Context-based graphical modeling for wavelet domain signal processing
نویسندگان
چکیده
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.
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