Classification of Polarimetric SAR Image Based on Four-component Scattering Model

An improved classification algorithm is proposed to deal with polarimetric synthetic aperture radar(POLSAR) images.This algorithm is based on a four-component scattering model,compared to the three-component(surface,double-bounce and volume) model introduced by Freeman and Durden,the four-component scattering model introduces the helix scattering as its fourth component,which can describe complex terrains and man-made targets in urban areas;so the four-component scattering model can deal with general scattering cases.In addition,this algorithm emphasizes the existence of pixels with mixed scattering mechanism,and applies the result of the four-component decomposition as feature vector to initial merging and the final iterative classifier.We use L-band AIRSAR data to demonstrate this improved method;and the experimental result verifies the effectiveness of this improved algorithm.