Spectral-spatial classification of polarimetric SAR data using morphological profiles

Morphological profiles (MPs) have been successfully used as tools to combine spectral and spatial information for classification of remote sensing data [1-5]. However, the previous applications have been limited to the multi-/ hyper-spectral data analysis. In this study, we extend the use of morphological profiles for classifying polarimetric synthetic aperture radar (POLSAR) data. An MP of a gray-level image (or a feature) is a sequence generated with the morphological opening by reconstruction and closing by reconstruction operations, using structuring elements of increasing size. An extended morphological profile (EMP) is constructed by stacking the MPs built using different features. An extended morphological attribute profile (EMAP) is an extension of the EMP where the profiles are created by application of attribute filters [6].