Wavelet Folding and Decorrelation Across the Scale

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dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)en_US
dc.citation.firstpage544
dc.citation.lastpage547
dc.citation.locationIstanbul, Turkeyen_US
dc.citation.volumeNumber1en_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.authorWells, R.O.en_US
dc.contributor.authorTian, Jun Fengen_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:36:17Z
dc.date.available2007-10-31T00:36:17Z
dc.date.issued2000-06-01en
dc.date.modified2006-06-20en_US
dc.date.note2006-06-07en_US
dc.date.submitted2000-06-01en_US
dc.descriptionConference Paperen_US
dc.description.abstractThe discrete wavelet transform (DWT) gives a compact multiscale representation of signals and provides a hierarchical structure for signal processing. It has been assumed the DWT can fairly well decorrelate real-world signals. However a residual dependency structure still remains between wavelet coefficients. It has been observed magnitudes of wavelet coefficients are highly correlated, both across the scale and at neighboring spatial locations. In this paper we present a wavelet folding technique, which folds wavelet coefficients across the scale and removes the across-the-scale dependence to a larger extent. It produces an even more compact signal representation and the energy is more concentrated in a few large coefficients. It has a great potential in applications such as image compression.en_US
dc.identifier.citationR. G. Baraniuk, R. Wells and J. F. Tian, "Wavelet Folding and Decorrelation Across the Scale," vol. 1, 2000.
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.2000.862039en_US
dc.identifier.urihttps://hdl.handle.net/1911/19714
dc.language.isoeng
dc.subject.otherDSP for Communicationsen_US
dc.titleWavelet Folding and Decorrelation Across the Scaleen_US
dc.typeConference paper
dc.type.dcmiText
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