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- W2154688547 abstract "Multichannel imaging systems provide several observations of the same scene which are often corrupted by noise. In this paper, we are interested in multispectral image denoising in the wavelet domain. We adopt a multivariate statistical approach in order to exploit the correlations existing between the different spectral components. Our main contribution is the application of Stein's principle to build a new estimator for arbitrary multichannel images embedded in additive Gaussian noise. Simulation tests carried out on optical satellite images show that the proposed method outperforms conventional wavelet shrinkage techniques." @default.
- W2154688547 created "2016-06-24" @default.
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- W2154688547 creator A5090426136 @default.
- W2154688547 date "2005-11-01" @default.
- W2154688547 modified "2023-10-15" @default.
- W2154688547 title "Building robust wavelet estimators for multicomponent images using Stein's principle" @default.
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- W2154688547 doi "https://doi.org/10.1109/tip.2005.857247" @default.
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