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Abstract: A novel approach for noise reduction is presented. Similar to Donoho, we employ thresholding in some wavelet transform domain but use a nondecimated and consequently redundant wavelet transform instead of the usual orthogonal one. Another difference is the shift invariance as opposed to the traditional orthogonal wavelet transform. We show that this new approach can be interpreted as a repeated application of Donoho's original method. The main feature is, however, a dramatically improved noise... (Update)
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...The removal of the small coefficients thus results in noise removal. There are two wavelet based variants to handle white noise [3][6]: hard thresholding: coefficients on some or all scales that are below a certain threshold are set to zero, soft thresholding:...
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BibTeX entry: (Update)
@inproceedings{ guo95nonlinear,
author = "H. Guo and M. Lang and J. E. Odegard and C. S. Burrus",
title = "Nonlinear Processing of a Shift-Invariant {DWT} for Noise Reduction and Compression",
booktitle = "Proceedings of the International Conference on Digital Signal Processing",
month = "26--28",
address = "Limassol, Cyprus",
pages = "332--337",
year = "1995",
url = "citeseer.ist.psu.edu/lang95nonlinear.html" }
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