  We have developed a nonlocal algorithm for estimating polarimetric synthetic
aperture radar (PolSAR) covariance matrices on single-look complex (SLC) format
resolution. The algorithm is inspired by recent work with guided nonlocal means
(NLM) speckle filtering, where a co-registered optical image is used to aid the
filtering. Based on patch-wise dissimilarities in the SAR and optical domains
we set the weights used for the nonlocal average of the outer product of the
lexicographic target vectors which form the estimate. By use of this method we
show that the estimated covariance matrices preserve the local structure better
than previous filtering methods and improve the separation of live from
defoliated and dead forest. The detail preserving nature of the algorithm also
means that it can be applicable in other settings where preserving the SLC
format resolution is necessary.
