Hidden Markov models for wavelet-based blind source separation

In this paper, we consider the problem of blind source separation in the wavelet domain. We propose a Bayesian estimation framework for the problem where different models of the wavelet coefficients are considered: the independent Gaussian mixture model, the hidden Markov tree model, and the context...

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Veröffentlicht in:	IEEE transactions on image processing 2006-07, Vol.15 (7), p.1887-1899
Hauptverfasser:	Ichir, M.M., Mohammad-Djafari, A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Bayesian analysis Bayesian estimation Bayesian methods Blind source separation Blinds Computer Graphics Computer Science Computer Simulation Context modeling Detection, estimation, filtering, equalization, prediction Engineering Sciences Exact sciences and technology Hidden Markov models hidden Markov models (HMMs) Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing image separation and denoising Imaging, Three-Dimensional - methods Information Storage and Retrieval - methods Information, signal and communications theory Laws Markov analysis Markov Chains Markov processes Mathematical models Mathematical Physics Mathematics Miscellaneous Models, Statistical Monte Carlo methods Noise level Noise reduction Numerical Analysis, Computer-Assisted Physics Separation Signal and communications theory Signal and Image processing Signal processing Signal Processing, Computer-Assisted Signal representation. Spectral analysis Signal to noise ratio Signal, noise source separation and independent component analysis Stochastic Processes Studies Telecommunications and information theory Wavelet Wavelet coefficients Wavelet domain
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