An information theory based image processing chain for change detection in Earth Observation

The paper presents an information theory approach for change detection, using Earth observation images. Correlation coefficient and Kullback-Leibler divergence are used as similarity measures allowing to find out where did change occur. Further, for an image characterization method, rate distortion theory is implemented to delimitate image complex regions, with high probability to have changed.