A Multiscale Framework for Challenging Discrete Optimization

Shai Bagon; Meirav Galun

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arXiv · 1210.7070

A Multiscale Framework for Challenging Discrete Optimization

Shai Bagon·Meirav Galun

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Abstract

Current state-of-the-art discrete optimization methods struggle behind when it comes to challenging contrast-enhancing discrete energies (i.e., favoring different labels for neighboring variables). This work suggests a multiscale approach for these challenging problems. Deriving an algebraic representation allows us to coarsen any pair-wise energy using any interpolation in a principled algebraic manner. Furthermore, we propose an energy-aware interpolation operator that efficiently exposes the multiscale landscape of the energy yielding an effective coarse-to-fine optimization scheme. Results on challenging contrast-enhancing energies show significant improvement over state-of-the-art methods.

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BibTeX RIS

Shai Bagon, Meirav Galun. 2012-11-02. A Multiscale Framework for Challenging Discrete Optimization. https://arxiv.org/abs/1210.7070

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