  This paper presents a new approach for filter design based on stochastic
distances and tests between distributions. A window is defined around each
pixel, overlapping samples are compared and only those which pass a
goodness-of-fit test are used to compute the filtered value. The technique is
applied to intensity SAR data with homogeneous regions using the Gamma model.
The proposal is compared with the Lee's filter using a protocol based on Monte
Carlo. Among the criteria used to quantify the quality of filters, we employ
the equivalent number of looks, line and edge preservation. Moreover, we also
assessed the filters by the Universal Image Quality Index and the Pearson's
correlation on edges regions.
