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Title:
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Hidden Markov Models for Wavelet-based Signal Processing |
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Author:
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Crouse, Matthew; Baraniuk, Richard G.; Nowak, Robert David
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Type:
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Conference Paper |
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Citation:
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M. Crouse, R. G. Baraniuk and R. D. Nowak,"Hidden Markov Models for Wavelet-based Signal Processing," in Asilomar Conference on Signals, Systems, and Computers,, pp. 1029-1035. |
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Abstract:
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Current wavelet-based statistical signal and image processing techniques such as shrinkage and filtering treat the wavelet coefficients as though they were statistically independent. This assumption is unrealistic; considering the statistical dependencies between wavelet coefficients can yield substantial performance improvements. In this paper we develop a new framework for wavelet-based signal processing that employs hidden Markov models to characterize the dependencies between wavelet coefficients. To illustrate the power of the new framework, we derive a new signal denoising algorithm that outperforms current scalar shrinkage techniques. |
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Date Published:
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1996-11-01 |
