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Nucleosynth (talk | contribs) mention efficiency |
Nucleosynth (talk | contribs) note about energy / probability correspondence |
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As applied in the field of [[computer vision]], '''[[Cut (graph theory)|graph cuts]]''' can be employed to [[Polynomial time|efficiently]] solve a wide variety of low-level computer vision problems, such as image [[smoothing]], the stereo [[correspondence problem]], and many other computer vision problems that can be formulated in terms of [[energy minimization]]. Such energy minimization problems can be [[Reduction (complexity)|reduced]] to instances of the [[maximum flow problem]] in a [[Graph (mathematics)|graph]] (and thus, by the [[max-flow min-cut theorem]], define a minimal cut of the graph). Under most formulations of such problems in computer vision, the minimum energy solution corresponds to the [[MAP estimate|maximum a posteriori estimate]] of a solution.
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