Information-Theoretic Analysis of Dependencies Between Curvelet Coefficients

This paper reports an information-theoretic analysis of the inter-scale, inter-orientation and inter-location dependencies that exist between curvelet coefficients. We show that the marginal statistics of these coefficients can be accurately modeled using generalized Gaussian density functions. Though generally decorrelated, we find that curvelets exhibit unusually high dependencies in intra-band local micro-neighborhoods, of a magnitude not found for instance in classical wavelets. Furthermore, dependencies are subject to and decrease with increasing orientation and location differences. Finally, we conclude that intra-band coefficient dependencies are stronger than either their inter-scale or inter-direction counterparts.