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dc.contributor.authorLi, Changen_US
dc.date.accessioned2007-05-15T15:23:57Z
dc.date.available2007-05-15T15:23:57Z
dc.date.issued1997-06-01T00:00:00Zen_US
dc.identifier.urihttp://hdl.handle.net/1993/949
dc.description.abstractBy using the wavelets and curvature, I tried to get a high quality compact representation of a surface. I get better results than simple Haar wavelets with curvature subdivision and Local Haar wavelets on the mathematical range data surface. To estimate the curvature of a curve represented by discrete data, a three point algorithm is developed. A normal approximation algorithm and an algorithm to estimate the Gaussian curvature are also developed for surface. The latter algorithm has a stable and fast convergence. To present background knowledge, I describe the multiresolution analysis with matrix and filter bank representation, the endpoint-interpolating B-spline wavelets, and basics of differential geometry. Several selection strategies for wavelets such as threshold and $\rm L\sp2$ measurement are presented and tested. A simple location mapping algorithm for Haar wavelets is also studied. Finally I discuss the conclusions and future work.en_US
dc.format.extent3736563 bytes
dc.format.extent184 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleWavelets and the use of curvature to approximate surfacesen_US
dc.typeinfo:eu-repo/semantics/masterThesis
dc.typemaster thesisen_US
dc.degree.disciplineComputer Scienceen_US
dc.degree.levelMaster of Science (M.Sc.)en_US


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