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dc.contributor.authorRout, Satyabrataen_US
dc.date.accessioned2014-03-14T20:45:28Z
dc.date.available2014-03-14T20:45:28Z
dc.date.issued2003-08-21en_US
dc.identifier.otheretd-09172003-111540en_US
dc.identifier.urihttp://hdl.handle.net/10919/35084
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_US
dc.publisherVirginia Techen_US
dc.relation.haspartEtdset.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectperiodic extensionen_US
dc.subjectDWT implementationen_US
dc.subjectbiorthogonal waveleten_US
dc.subjectorthogonal waveleten_US
dc.subjectsymmetric extensionen_US
dc.titleOrthogonal vs. Biorthogonal Wavelets for Image Compressionen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
dc.contributor.committeechairBell, Amy E.en_US
dc.contributor.committeememberAbbott, A. Lynnen_US
dc.contributor.committeememberWoerner, Brain D.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-09172003-111540/en_US
dc.date.sdate2003-09-17en_US
dc.date.rdate2003-09-19
dc.date.adate2003-09-19en_US


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