Abstract
Wavelet analysis is a modern mathematical technique that extends Fourier analysis. We study the removal of additive, Gaussian white noise from signals and images via the wavelet transform. We first discuss aspects of wavelet theory that are relevant for this application. Then we review recent wavelet based methods for noise reduction. We focus on the wavelet extrema technique developed by Mallat and on a variant by Xu, Healy and Weaver. We also comment on the extension of these methods.
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© 1995 Springer Science+Business Media Dordrecht
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Malfait, M., Roose, D. (1995). Experiments with a Wavelet Based Image Denoising Method. In: Singh, S.P. (eds) Approximation Theory, Wavelets and Applications. NATO Science Series, vol 454. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8577-4_25
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DOI: https://doi.org/10.1007/978-94-015-8577-4_25
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4516-4
Online ISBN: 978-94-015-8577-4
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