Review of Methods Inspired by Algebraic-Multigrid for Data and Image Analysis Applications

Review of Methods Inspired by Algebraic-Multigrid for Data and Image Analysis Applications

Year:    2015

Numerical Mathematics: Theory, Methods and Applications, Vol. 8 (2015), Iss. 2 : pp. 283–312

Abstract

Algebraic Multigrid (AMG) methods were developed originally for numerically solving Partial Differential Equations (PDE), not necessarily on structured grids. In the last two decades solvers inspired by the AMG approach, were developed for non PDE problems, including data and image analysis problems, such as clustering, segmentation, quantization and others. These solvers share a common principle that there is a crosstalk between fine and coarse representations of the problems, with flow of information in both directions, fine-to-coarse and coarse-to-fine. This paper surveys some of these problems and the AMG-inspired algorithms for their solution.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/nmtma.2015.w14si

Numerical Mathematics: Theory, Methods and Applications, Vol. 8 (2015), Iss. 2 : pp. 283–312

Published online:    2015-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    30

Keywords: