Approximate continuous wavelet transform with an application to noise reduction

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dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)en_US
dc.citation.locationSeattle, WAen_US
dc.contributor.authorLewis, James M.en_US
dc.contributor.authorBurrus, C. Sidneyen_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:51:27Zen_US
dc.date.available2007-10-31T00:51:27Zen_US
dc.date.issued1998-05-20en_US
dc.date.modified2001-10-05en_US
dc.date.note2001-10-05en_US
dc.date.submitted1998-05-20en_US
dc.descriptionConference paperen_US
dc.description.abstractWe describe a generalized scale-redundant wavelet transform which approximates a dense sampling of the continuous wavelet transform (CWT) in both time and scale. The dyadic scaling requirement of the usual wavelet transform is relaxed in favor of an approximate scaling relationship which in the case of a Gaussian scaling function is known to be asymptotically exact and irrational. This scheme yields an arbitrarily dense sampling of the scale axis in the limit. Similar behavior is observed for other scaling functions with no explicit analytic form. We investigate characteristics of the family of Lagrange interpolating filters (related to the Daubechies family of compactly-supported orthonormal wavelets), and finally present applications of the transform to denoising and edge detection.en_US
dc.identifier.citationJ. M. Lewis and C. S. Burrus, "Approximate continuous wavelet transform with an application to noise reduction," 1998.en_US
dc.identifier.urihttps://hdl.handle.net/1911/20055en_US
dc.language.isoengen_US
dc.subjectcontinuous wavelet transform (CWT)en_US
dc.subjectnoise reductionen_US
dc.subjectGaussianen_US
dc.subjectDaubechiesen_US
dc.subjectorthonormal waveleten_US
dc.subjectedge detectionen_US
dc.subject.keywordcontinuous wavelet transform (CWT)en_US
dc.subject.keywordnoise reductionen_US
dc.subject.keywordGaussianen_US
dc.subject.keywordDaubechiesen_US
dc.subject.keywordorthonormal waveleten_US
dc.subject.keywordedge detectionen_US
dc.titleApproximate continuous wavelet transform with an application to noise reductionen_US
dc.typeConference paperen_US
dc.type.dcmiTexten_US
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