THE PRINCIPLE OF SPECKLE FILTERING IN POLARIMETRIC SAR IMAGERY

The principle of speckle reduction in polarimetry is reconsidered. It is shown that polarimetric data can be speckle reduced if and only if all the elements of the Mueller matrix are filtered, which is equivalent to filtering the scattering vector covariance matrix. Assuming that speckle is multiplicative and stationary, the algorithms proposed in [1] and [2] are extended to filter the covariance matrix of reciprocal and nonreciprocal targets on one-look and multilook images. The problem of estimation of the first- and second-order statistics of the four-channel speckle vector is discussed, and a solution is proposed for one-look and multilook images.