A MMSE SPECKLE FILTER FOR FULL RESOLUTION SAR POLARIMETRIC DATA

The usual polarimetric speckle filters optimally combine the polarization channels into a single image [10] or only restore the radiometric information [8], i.e., only the four I(hh), I(vv), I(hv) and I(vh) backscattered intensities (or the three I(hh), I(vv), I(hv) intensities in the reciprocal case). The phase differences for one-look images axe not restored. This implies a loss of information compared to the initial data, which contain five independent real parameters plus one absolute phase for the one-look scattering matrix format in the reciprocal case. In this paper we develop a fully polarimetric minimum mean square error (MMSE) filter under the multiplicative speckle noise model assumption for one-look images. This model assumes the data to be the product of the non-stationary ''unspeckled'' signal by statistically independent speckle noise, characterized by the covariance matrix of a stationary complex multivariate Gaussian random process, representing the sensor effects. For each pixel, one obtains on output of the filtering process a complex ''unspeckled'' scattering matrix and in addition, the complex degrees of coherence between the polarization channels. Furthermore, an adaptive window of sufficient size, defined by the coefficient of variation and various contrast ratios computed in an improved span image, allows the detection of structural features, ensuring reliable statistics for input parameters. Hence, speckle is highly reduced and the spatial resolution is not degraded. The extra information brought up by the filter (phase differences and magnitude of degrees of coherence) will be illustrated in this paper on NASA/JPL data.