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- W2131084499 abstract "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. 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 algorithm for signal estimation in nonGaussian noise." @default.
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- W2131084499 date "2002-11-22" @default.
- W2131084499 modified "2023-09-22" @default.
- W2131084499 title "Signal estimation using wavelet-Markov models" @default.
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- W2131084499 doi "https://doi.org/10.1109/icassp.1997.604601" @default.
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