Clutter discrimination in polarimetric and interferometric synthetic aperture radar imagery

Many synthetic aperture radar (SAR) images contain extended regions of apparently homogeneous clutter arising from areas of vegetation or uniformly driven expanses of water. These regions may contain localized clutter variations resulting from the presence of features of ecological interest, such as changes in vegetation density due to environmental effects or damping of the sea surface by pollutants. Alternatively such clutter variations may be due to the signatures of partially concealed land-based or maritime military targets. It is thus of interest to develop techniques which can discriminate localized clutter features from the background clutter. Multiple-channel SAR systems can provide several images of a scene of this type which contain complementary sets of information. These can be combined to generate a single enhanced image of the scene in which it is possible to discriminate more effectively among the features it contains. In this paper a unified discussion of multi-channel enhancement techniques, which make use of varying degrees of knowledge regarding the statistical characteristics of the image features, is presented.