A Supervised Classification Method of Polarimetric Sythetic ApertureRadar Data Using Watershed Segmentation and Decision Tree C5.0

Objective A supervised classification method of polarimetric sythetic aperture radar(PoSAR)data u-sing watershed segmentation and Decision Tree C5.0with many polarimetric channels is proposed.First,the PolSAR data was filtered using the 5×5refined Lee PolSAR speckle filter,and then a PauliRGB color image and many polarimetric channels were obtained using various algorithms.Then,wa-tershed segmentation on gradient map was made for a homogeneous area and the features of every areawere worked out.At last,Decision tree C5.0was used to deal with the data.The result shows thatthis method performs better than methods based on pixels,and the classification accuracy is improvedwith the quantity of polarimetric characteristic increase.