Many important physical processes in fields such as materials science, ecology, structural biology, and clinical pathology involve the study of microscopic structures – from formation and propagation to steady-state behavior. The study of these phenomena is often very slow, creating an enormous need for accurate computer simulation of the underlying processes. In this paper, we provide a robust algorithm for simulation of images of such processes modeled by a Gibbs distribution. As part of our rare-event simulation solution, we adapt an importance sampling technique specifically for Markov random fields. We conclude by showing results of simulation of images of abnormal grain growth in poly-crystalline materials and NiCrAl super-alloy precipitates that find applications in several important real-life fields such as aircraft material design.