Generalized Recurrence Plots for the analysis of images from spatially distributed systems

We propose a new method for the analysis of images showing patterns emerging from the evolution of spatially distributed systems. The generalized recurrence plot (GRP) and the generalized recurrence quantification analysis (GRQA) are exploited for the investigation of such patterns. We focus on snapshots of spatio-temporal processes such as the formation of Turing structures and traveling waves in the Belousov-Zhabotinsky reaction, satellite images of spatial chlorophyll distribution in seas and oceans (similar to turbulent flows), colonies of Dyctiostelium discoideum, fractals, and noise. The method is based on the GRP and GRQA and particularly on the measures determinism (DET) and entropy (ENT), providing a new criterion for the assessment and classification of images based on the simultaneous evaluation of their global and local structure. The DET-ENT diagram is introduced and compared with the classical image analysis entropy defined on the pixels' values. The method proposed provides appealing performances in the case of images showing complex spatial patterns.