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dc.contributor.advisorSchaefer, Scott
dc.creatorManson, Josiah
dc.date.accessioned2015-01-09T20:50:37Z
dc.date.available2015-01-09T20:50:37Z
dc.date.created2014-05
dc.date.issued2014-04-30
dc.date.submittedMay 2014
dc.identifier.urihttps://hdl.handle.net/1969.1/152826
dc.description.abstractWhen drawing images onto a computer screen, the information in the scene is typically more detailed than can be displayed. Most objects, however, will not be close to the camera, so details have to be filtered out, or anti-aliased, when the objects are drawn on the screen. I describe new methods for filtering images and shapes with high fidelity while using computational resources as efficiently as possible. Vector graphics are everywhere, from drawing 3D polygons to 2D text and maps for navigation software. Because of its numerous applications, having a fast, high-quality rasterizer is important. I developed a method for analytically rasterizing shapes using wavelets. This approach allows me to produce accurate 2D rasterizations of images and 3D voxelizations of objects, which is the first step in 3D printing. I later improved my method to handle more filters. The resulting algorithm creates higher-quality images than commercial software such as Adobe Acrobat and is several times faster than the most highly optimized commercial products. The quality of texture filtering also has a dramatic impact on the quality of a rendered image. Textures are images that are applied to 3D surfaces, which typically cannot be mapped to the 2D space of an image without introducing distortions. For situations in which it is impossible to change the rendering pipeline, I developed a method for precomputing image filters over 3D surfaces. If I can also change the pipeline, I show that it is possible to improve the quality of texture sampling significantly in real-time rendering while using the same memory bandwidth as used in traditional methods.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectfilteringen
dc.subjecttexture mappingen
dc.subjectmipmapen
dc.subjectrasterizationen
dc.subjectwaveletsen
dc.subjectsurface reconstructionen
dc.titleImproving Filtering for Computer Graphicsen
dc.typeThesisen
thesis.degree.departmentComputer Science and Engineeringen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorTexas A & M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberKeyser, John
dc.contributor.committeeMemberChai, Jinxiang
dc.contributor.committeeMemberPetrova, Guergana
dc.type.materialtexten
dc.date.updated2015-01-09T20:50:37Z
local.etdauthor.orcid0000-0002-9095-4275


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