Polsar region classifier based on stochastic distances and hypothesis tests

Wagner Silva, Corina Freitas, Sidnei Sant'Anna, Alejandro C. Frery
2012 2012 IEEE International Geoscience and Remote Sensing Symposium  
This work presents a region based classifier for Polarimetric SAR (PolSAR) images. The classifier uses the stochastic distances derived from the complex Wishart Model, obtained from the h-φ family of divergences. Adittionaly, a hypothesis test derived from the stochastic distance is also employed in the classification process. The region based classifier, using the Bhattacharyya distance, was applied to a polarimetric SIR-C image from an agricultural area in northeastern Brazil. The region
more » ... classification result significantly overperformed the a pixel based/contextual PolSAR classification based on the Maximum Likelihood/Iterated Conditional Modes. Such evidence lead us to conclude that the region based stochastic distance and hypothesis test classifier offers a good potential at identifying the land cover classes on a PolSAR image.
doi:10.1109/igarss.2012.6351256 dblp:conf/igarss/SilvaFSF12 fatcat:bfqtnlx7jve2jiaooa3hueu3ve