PolSAR image segmentation — Advanced statistical modelling versus simple feature extraction

Abstract

In recent years, we have presented many algorithms for polarimetric SAR image segmentation that show the continually improving developments in the field. However, there are two distinct and divergent approaches - one using highly flexible textured models for the covariance matrix statistics (such as the Wishart, K-Wishart, and U-distribution), and the other using simple features extracted from such data (the Extended Polarimetric Feature Space method). In this study we will present a summary and comparison of both approaches and discuss the pros and cons for each with respect to image segmentation applications.