On Single-Look Multivariate $ {\cal G}$ Distribution for PolSAR Data

Salman Khan,Raffaella Guida

doi:10.1109/jstars.2012.2202557

Abstract

For many applications where High Resolution (HR) Synthetic Aperture Radar (SAR) images are required, like urban structures detection, road map detection, marine structures and ship detection etc., single-look processing of SAR images may be desirable. The G family of distributions have been known to fit homogeneous to extremely heterogeneous Polarimetric SAR (PolSAR) data very well and can be very useful for processing single-look images. The multi-look polarimetric G distribution has a limitation that it does not reduce to single-look form for (multivariate) PolSAR data. This paper presents the new single-look polarimetric G distribution, which reduces to its two well-known special forms, the single-look K p and G p 0 distributions, when the domain of its parameters are restricted. The significance of this distribution becomes evident as it fits X- & S-band sub-meter resolution (<; 1 m 2 ) PolSAR data (acquired over the same scene at the same time in X- & S-bands) better than the G p 0 & K p distributions, while it fits the X-band decameter resolution (10 m 2 ) PolSAR data as good as the G p 0 distribution. Numerical Maximum Likelihood Estimation (MLE) method for parameter estimation of multivariate G, G p 0 , and K p distributions is proposed. Simulated PolSAR data has been generated to validate the convergence and accuracy of maximum likelihood parameter estimates to values corresponding to globally maximum likelihood. A new iterative algorithm for accurate estimation of speckle covariance matrix is also proposed.

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