Statistical Image Modeling and Processing Using Wavelet-Domain Hidden Markov Models - Nonlinear Signal and Image Processing: Theory, Methods and Applications - page 383

texture characterization than HMT. It was shown that the combi-
nation of JMCMS and HMT-3S provides the best segmentation re-
sults among all tested methods, as measured by the three numerical
criteria.

•

We point out that wavelet-domain HMMs are useful in texture anal-
ysis and texture synthesis applications. Unlike with image denois-
ing, hierarchical tree-structured HMMs such as HMT or HMT-3S
are desired; they regard the whole wavelet subtree as one instance
of the statistical model. Meanwhile, efficient texture processing al-
gorithms are also very important to the applications of wavelet-
domain HMMs for texture-related processing. This may include
maximum likelihood-based texture classification and maximum
likelihood-based texture synthesis.

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