dc.contributor.author Li, Chang en_US dc.date.accessioned 2007-05-15T15:23:57Z dc.date.available 2007-05-15T15:23:57Z dc.date.issued 1997-06-01T00:00:00Z en_US dc.identifier.uri http://hdl.handle.net/1993/949 dc.description.abstract By 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.extent 3736563 bytes dc.format.extent 184 bytes dc.format.mimetype application/pdf dc.format.mimetype text/plain dc.language.iso eng en_US dc.rights info:eu-repo/semantics/openAccess dc.title Wavelets and the use of curvature to approximate surfaces en_US dc.type info:eu-repo/semantics/masterThesis dc.type master thesis en_US dc.degree.discipline Computer Science en_US dc.degree.level Master of Science (M.Sc.) en_US
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