Mimick capacity of Generalized Gamma distribution for high resolution SAR image statistical modeling

In this paper we investigate the capacity of the Generalized Gamma distribution to mimick (or imitate) thanks to its three parameters other useful SAR distributions. We first compare it with the Fisher distribution when mimicking a K distribution of reference, thanks to the log-cumulant approach and through a Kullback-Leibler divergence. We then study how the Generalized Gamma distribution can imitate a Log-Normal distribution as asymtotic limit.