Graph-cut segmentation of polarimetric SAR images

Segmentation of Synthetic Aperture Radar (SAR) images is often only understood as the partitioning of the image into rather small regions which are homogeneous with respect to scattering processes. This paper proposes an adaption of the graph-cut image segmentation framework to the unique characteristics of polarimetric SAR images by using a Wishart-distribution based distance measure for local segmentation cues and simple, real-valued features derived from the complex-valued coherency matrix. The proposed method is evaluated on different polarimetric SAR images, for different objects of interest, and with a wide range of parameters. The results show that the proposed framework is able to derive accurate object/non-object segmentations. Best results are obtained for forest areas by usage of a log-transform of the polarimetric intensities.