Similarity and dissimilarity measures for comparison of propagation patterns

This study examines several different similarity and dissimilarity measures for comparing propagation patterns. Typically used in image registration problems, we evaluate their utility here using propagation patterns simulated using a parabolic equation simulation. High correspondence between certain pairings of measures may indicate structural similarity or the absence of noise, and strong correspondence among all measures reduces ambiguity in the best-matching pattern. Incorporating multiple evaluation measures thereby improves the fidelity of the pattern comparison.