On the use of multilook amplitude K distribution for SAR image analysis

The K distribution has been used as a flexible tool for the modelling of SAR data over non-homogeneous areas. It is characterized by three real-valued parameters; one of these parameters, the number of looks, is related to the kind of processing the raw data suffer in order to become an image. This distribution has been mostly used for one look data. In this paper the multilook case is considered for both quadratic and linear detections. A closed (recursive) computational form is provided for the K cumulative distribution function, as well as the estimators derived from the substitution method. The sensitivity of the cumulative distribution function, with respect to possible discretizations of the parameters due to limitations imposed by the recursive form is discussed. The recursive form of the cumulative distribution function of K multilook random variables is used to perform the Kolmogorov-Smirnov (KS) test of goodness of fit over SAREX data. It is shown that, mainly for forest data, the fit with the K multilook distribution is superior to some of other distributions that frequently appear in the literature. Specifically, the use of the normal distribution for this kind of data is discarded systematically