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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 ...
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 ...
Multiscale Edge Grammars for Complex Wavelet Transforms
Wavelet domain algorithms have risen to the forefront of image processing. The power of these algorithms is derived from the fact that the wavelet transform restructures the image in a way that makes statistical modeling ...