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AMC
2007

Geometric multigrid for high-order regularizations of early vision problems

13 years 10 months ago
Geometric multigrid for high-order regularizations of early vision problems
The surface estimation problem is used as a model to demonstrate a framework for solving early vision problems by high-order regularization with natural boundary conditions. Because the application of algebraic multigrid is usually constrained by an M-matrix condition which does not hold for discretizations of high-order problems, a geometric multigrid framework is developed for the efficient solution of the associated optimality systems. It is shown that the convergence criteria of [5] are met, and in particular the general elliptic regularity required is proved. Further, the Galerkin formalism is used together with a multi-colored ordering of unknowns to permit vectorization of a symmetric Gauss-Seidel relaxation in image processing systems. The implementation is analyzed computationally and inaccuracies are corrected by lumping and by proper floating point representations. Direct one-dimensional calculations are used to estimate the effect of regularization order, regularization s...
Stephen L. Keeling, Gundolf Haase
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2007
Where AMC
Authors Stephen L. Keeling, Gundolf Haase
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