Information Theory Approach to Crystallographic Symmetry Classifications of Noisy 2D Periodic Images

An information theory inspired approach, i.e. utilization of Geometric Akaike Information Criteria (G-AICs), individual Akaike weights, and products of Akaike weights, allows for objective crystallographic symmetry classification of images that are more or less periodic in two dimensions (2D). The combined usage of G-AICs for Bravais lattice types and plane symmetry groups should enable successful classifications even in the presence of severe pseudo-symmetry challenges.