Abstract
Partial differential equations (PDEs) have recently shown to be very promising for image interpolation and compression. Inspired from this work, we present a PDE based approach to interpolation of surfaces from scattered point sets using the geometric diffusion equation. Triangulated surfaces are considered in the discrete setting, and the geometric diffusion equation is discretized by the finite element method directly on the triangular mesh. Furthermore, a PDE based method for lossy compression of triangulated surfaces is presented. The idea is to store only a few relevant vertex coordinates in the encoding step. In the decoding step, the remaining vertices are reconstructed by solving the geometric diffusion equation. Finally, two modified reconstruction methods are proposed that are shown to improve the compression quality for both images and surfaces. These reconstruction methods approximate instead of interpolating, and have links to Hopscotch methods for the numerical solution of PDEs. Experiments are presented illustrating that results of high quality can be obtained using simple geometric diffusion without any information on surface normals.
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Bae, E., Weickert, J. (2010). Partial Differential Equations for Interpolation and Compression of Surfaces. In: Dæhlen, M., Floater, M., Lyche, T., Merrien, JL., Mørken, K., Schumaker, L.L. (eds) Mathematical Methods for Curves and Surfaces. MMCS 2008. Lecture Notes in Computer Science, vol 5862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11620-9_1
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DOI: https://doi.org/10.1007/978-3-642-11620-9_1
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