We propose a new Γ-convergent discrete approximation of the Mumford-Shah functional. The discrete functionals act on functions defined on stationary stochastic lattices and take into account general finite differences through a non-convex potential. In this setting the geometry of the lattice strongly influences the anisotropy of the limit functional. Thus we can use statistically isotropic lattices and stochastic homogenization techniques to approximate the vectorial Mumford-Shah functional in any dimension. version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ Remark 2.3. We also make use of the associated Voronoi tessellation V(ω) = {C(x)} x∈L(ω) , where the (random) Voronoi cells with nuclei x ∈ L(ω) are defined asIf L(ω) is admissible, then [6, Lemma 2.3] yields the inclusions B r 2 (x) ⊂ C(x) ⊂ B R (x). Next we introduce some notions from ergodic theory that build the basis for stochastic homogenization.Definition 2.4. We say that a family of measurable functions {τ z } z∈Z d , τ z : Ω → Ω, is an additive group action on Ω if τ 0 = id and τ z1+z2 = τ z2 • τ z1 for all z 1 , z 2 ∈ Z d .An additive group action is called measure preserving ifIn terms of a stochastic lattice the probabilistic properties read as follows:Definition 2.5. A stochastic lattice L is said to be stationary if there exists an additive, measure preserving group action {τ z } z∈Z d on Ω such that for all z ∈ Z d L • τ z = L + z.