Noise Reduction Using an Undecimated Discrete Wavelet Transform

dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE Signal Processing Lettersen_US
dc.contributor.authorLang, Markusen_US
dc.contributor.authorGuo, Haitaoen_US
dc.contributor.authorOdegard, Jan E.en_US
dc.contributor.authorBurrus, C. Sidneyen_US
dc.contributor.authorWells, R.O.en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:51:07Z
dc.date.available2007-10-31T00:51:07Z
dc.date.issued1995-01-15en
dc.date.modified2004-01-21en_US
dc.date.note2004-01-08en_US
dc.date.submitted1995-01-15en_US
dc.descriptionConference Paperen_US
dc.description.abstractA new nonlinear noise reduction method is presented that uses the discrete wavelet transform. Similar to Donoho and Johnstone, we employ thresholding in the wavelet transform domain but, following a suggestion by Coifman, we use an undecimated, shift-invariant, nonorthogonal wavelet transform instead of the usual orthogonal one. This new approach can be interpreted as a repeated application of the original Donoho and Johnstone method for different shifts. The main feature of the new algorithm is a significantly improved noise reduction compared to the original wavelet based approach, both the <i>l<sub>2</sub></i> error and visually, for a large class of signals. This is shown both theoretically as well as by experimental results.en_US
dc.identifier.citationM. Lang, H. Guo, J. E. Odegard, C. S. Burrus and R. Wells, "Noise Reduction Using an Undecimated Discrete Wavelet Transform," 1995.
dc.identifier.urihttps://hdl.handle.net/1911/20049
dc.language.isoeng
dc.subjectTemporary*
dc.subject.keywordTemporaryen_US
dc.subject.otherWavelet based Signal/Image Processingen_US
dc.titleNoise Reduction Using an Undecimated Discrete Wavelet Transformen_US
dc.typeConference paper
dc.type.dcmiText
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