Abstract:We introduce novel information-entropic variables-a Point Divergence Gain (Ω (l→m) α ), a Point Divergence Gain Entropy (I α ), and a Point Divergence Gain Entropy Density (P α )-which are derived from the Rényi entropy and describe spatio-temporal changes between two consecutive discrete multidimensional distributions. The behavior of Ω (l→m) α is simulated for typical distributions and, together with I α and P α , applied in analysis and characterization of series of multidimensional datasets of computer-based and real images.