Efficient algorithms for image and high dimensional data processing using eikonal equation on graphs

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Abstract

In this paper we propose an adaptation of the static eikonal equation over weighted graphs of arbitrary structure using a framework of discrete operators. Based on this formulation, we provide explicit solutions for the L1, L2 and L∞ norms. Efficient algorithms to compute the explicit solution of the eikonal equation on graphs are also described. We then present several applications of our methodology for image processing such as superpixels decomposition, region based segmentation or patch-based segmentation using non-local configurations. By working on graphs, our formulation provides an unified approach for the processing of any data that can be represented by a graph such as high-dimensional data. © 2010 Springer-Verlag.

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Desquesnes, X., Elmoataz, A., Lézoray, O., & Ta, V. T. (2010). Efficient algorithms for image and high dimensional data processing using eikonal equation on graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6454 LNCS, pp. 647–658). https://doi.org/10.1007/978-3-642-17274-8_63

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