Adaptive Wavelet Transforms for Image Coding using Lifting

dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameData Compression Conferenceen_US
dc.citation.firstpage537
dc.citation.locationSnowbird, UTen_US
dc.contributor.authorClaypoole, Roger L.en_US
dc.contributor.authorDavis, Geoffreyen_US
dc.contributor.authorSweldens, Wimen_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:40:13Z
dc.date.available2007-10-31T00:40:13Z
dc.date.issued1998-03-01en
dc.date.modified2006-06-07en_US
dc.date.note2006-06-07en_US
dc.date.submitted1998-03-01en_US
dc.descriptionConference paperen_US
dc.description.abstractSummary form only given. Image compression relies on efficient representations of images, and within smooth image regions, the wavelet transform provides such a representation. However, near edges, wavelet coefficients decay slowly and are expensive to code. We focus on improving the transform by incorporating adaptivity. Construction of nonlinear filter banks has been discussed, but the question of how to utilize the nonlinearities remained. We answer this question by describing our transform via lifting. Lifting provides a spatial domain framework for the wavelet transform. In the lifting formalism, wavelet coefficients are seen as prediction residuals from a linear prediction operation. Wavelet coefficients are large near edges because the linear predictors are built to interpolate low order polynomials. Our goal is to avoid this problem by adapting the predictor based on local image properties. In smooth regions of the image, we use high order polynomial predictors. We adaptively reduce the prediction order to avoid attempting to predict values across discontinuities.en_US
dc.identifier.citationR. L. Claypoole, G. Davis, W. Sweldens and R. G. Baraniuk, "Adaptive Wavelet Transforms for Image Coding using Lifting," 1998.
dc.identifier.urihttps://hdl.handle.net/1911/19803
dc.language.isoeng
dc.subject.otherDSP for Communicationsen_US
dc.titleAdaptive Wavelet Transforms for Image Coding using Liftingen_US
dc.typeConference paper
dc.type.dcmiText
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