Orthogonal vs. Biorthogonal Wavelets for Image Compression

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dc.contributor.authorRout, Satyabrataen
dc.contributor.committeechairBell, Amy E.en
dc.contributor.committeememberAbbott, A. Lynnen
dc.contributor.committeememberWoerner, Brain D.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2014-03-14T20:45:28Zen
dc.date.adate2003-09-19en
dc.date.available2014-03-14T20:45:28Zen
dc.date.issued2003-08-21en
dc.date.rdate2003-09-19en
dc.date.sdate2003-09-17en
dc.description.abstractEffective image compression requires a non-expansive discrete wavelet transform (DWT) be employed; consequently, image border extension is a critical issue. Ideally, the image border extension method should not introduce distortion under compression. It has been shown in literature that symmetric extension performs better than periodic extension. However, the non-expansive, symmetric extension using fast Fourier transform and circular convolution DWT methods require symmetric filters. This precludes orthogonal wavelets for image compression since they cannot simultaneously possess the desirable properties of orthogonality and symmetry. Thus, biorthogonal wavelets have been the de facto standard for image compression applications. The viability of symmetric extension with biorthogonal wavelets is the primary reason cited for their superior performance. Recent matrix-based techniques for computing a non-expansive DWT have suggested the possibility of implementing symmetric extension with orthogonal wavelets. For the first time, this thesis analyzes and compares orthogonal and biorthogonal wavelets with symmetric extension. Our results indicate a significant performance improvement for orthogonal wavelets when they employ symmetric extension. Furthermore, our analysis also identifies that linear (or near-linear) phase filters are critical to compression performance---an issue that has not been recognized to date. We also demonstrate that biorthogonal and orthogonal wavelets generate similar compression performance when they have similar filter properties and both employ symmetric extension. The biorthogonal wavelets indicate a slight performance advantage for low frequency images; however, this advantage is significantly smaller than recently published results and is explained in terms of wavelet properties not previously considered.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-09172003-111540en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-09172003-111540/en
dc.identifier.urihttp://hdl.handle.net/10919/35084en
dc.publisherVirginia Techen
dc.relation.haspartEtdset.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectperiodic extensionen
dc.subjectDWT implementationen
dc.subjectbiorthogonal waveleten
dc.subjectorthogonal waveleten
dc.subjectsymmetric extensionen
dc.titleOrthogonal vs. Biorthogonal Wavelets for Image Compressionen
dc.typeThesisen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen
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