Abstract
Multigrid methods provide fast solvers for a wide variety of problems encountered in computer vision. Recent graphics hardware is ideally suited for the implementation of such methods, but this potential has not yet been fully realized. Typically, work in that area focuses on linear systems only, or on implementation of numerical solvers that are not as efficient as multigrid methods. We demonstrate that nonlinear multigrid methods can be used to great effect on modern graphics hardware. Specifically, we implement two applications: a nonlinear denoising filter and a solver for variational optical flow. We show that performing these computations on graphics hardware is between one and two orders of magnitude faster than comparable CPU-based implementations.
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Grossauer, H., Thoman, P. (2008). GPU-Based Multigrid: Real-Time Performance in High Resolution Nonlinear Image Processing. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds) Computer Vision Systems. ICVS 2008. Lecture Notes in Computer Science, vol 5008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79547-6_14
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DOI: https://doi.org/10.1007/978-3-540-79547-6_14
Publisher Name: Springer, Berlin, Heidelberg
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