A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix ...A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix Ω based on the eigenvalue decomposition of the coherency matrix of each band. A boxcar filter is then performed on the matrix Ω. The filtered data are put into a complex Wishart classifier. Finally, the effectiveness of the proposed method is demonstrated with JPL/AIRSAR multifrequency PolSAR data acquired over the Flevoland area.展开更多
基金supported in part by the National Natural Science Fundation of China(4117131761132008+1 种基金61490693)Aeronautical Science Foundation of China(20132058003)
文摘A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix Ω based on the eigenvalue decomposition of the coherency matrix of each band. A boxcar filter is then performed on the matrix Ω. The filtered data are put into a complex Wishart classifier. Finally, the effectiveness of the proposed method is demonstrated with JPL/AIRSAR multifrequency PolSAR data acquired over the Flevoland area.
