Comparison of nonlocal means despeckling based on stochastic measures

RAFAEL GRIMSON; NATALIA MORANDEIRA; ALEJANDRO FRERY

Milan

Simposio; International Geoscience and Remote Sensing Symposium 2015 (IGARSS 2015); 2015

IEEE

This work presents the use of stochastic measures of similarities as features with statistical significance for the design of despeckling nonlocal means filters. Assuming that the observations follow a Gamma model with two parameters (mean and number of looks), patches are compared by means of the Kullback-Leibler and Hellinger distances, and by their Shannon entropies. A convolution mask is formed using the p-values of tests that verify if the patches come from the same distribution. The filter performances are assessed using well-known phantoms, three measures of quality, and a Monte Carlo experiment with several factors. The proposed filters are contrasted with the Refined Lee and NL-SAR filters.