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Higher order levelable mrf energy minimization via graph cuts

Karcı, Mehmet Haydar
A feature of minimizing images of a class of binary Markov random field energies is introduced and proved. Using this, the collection of minimizing images of levels of higher order, levelable MRF energies is shown to be a monotone collection. This implies that these images can be combined to give minimizing images of the MRF energy itself. Due to the recent developments, second and third order binary MRF energies of the mentioned class are known to be exactly minimized by maximum flow/minimum cut computations on appropriately constructed graphs. With the aid of these developments an exact and efficient algorithm to minimize levelable second and third order MRF energies, which is composed of a series of maximum flow/minimum cut computations, is proposed and applications of the proposed algorithm to image restoration are given.