Multilook polarimetric SAR data probability density function estimation using a generalized form of multivariate K-distribution

In our previous work, the probability density function (pdf) of single-channel synthetic aperture radar (SAR) data was modelled as a generalized form of the univariate K-distribution in order to incorporate higher order moments in the pdf estimation. In this paper, we extend this univariate model to the multivariate case, the objective being the sample covariance matrix pdf estimation of multilook polarimetric SAR data. Applying the product model, and assuming the texture distribution as the Laguerre expansion of the gamma distribution, we derive this pdf, which is a generalized form of the well-known multivariate K-distribution. The resulting distributions are assessed quantitatively with respect to multilook fully polarimetric L-band SAR image data from which we conclude that the proposed pdf demonstrates an improved goodness of fit.