The theory of graph cuts, Cut (graph theory), was first applied in Computer vision in the "classic" 1989 paper by Greig, Porteous and Seheult of Durham University, UK, as referenced below.
In the statistical context of smoothing noisy, or corrupted, images, Greig, Porteous and Seheult showed how the maximum a posteriori estimate of a binary image can be obtained exactly by maximising the flow through an associated image network.
References
- D.M. Greig, B.T. Porteous, A.H. Seheult, Exact maximum a posteriori estimation for binary images, Journal of the Royal Statistical Society Series B, 271 - 279 (1989)