Data fusion of multiple polarimetric SAR images using discrete wavelet transform (DWT)

Data fusion is a very effective technique which can be applied to many remote sensing areas such as classification, monitoring of environmental surveillance and man-made target tracking. In this paper, we tested fusion of multiple frequency (C-, and L-band), multiple polarization (HH, HV and VV) and multiresolution data sets. One can obtain a polarimetric SAR data after enhancing spatial resolution through the image fusion process. In order to fuse multiple SAR data and high spatial resolution data, they have to be geometrically co-registered over the same target area and have the same pixel size (spatial registrations). At this stage, we used the nearest neighbor resampling to avoid spectral distortion by interpolation. Multiresolution polarimetric SAR image fusion was performed using the multiscale image fusion technique-discrete wavelet transform after spatial registrations. To evaluate the spectral fidelity of fused polarimetric SAR data, spectral dissimilarity was calculated at each wavelet decomposition level. The resulting classification map based on polarimetric feature vectors shows better class separation after application of fusion processing than without fusion. The polarimetric SAR data over the Gong-ju areas, tested in this research, were acquired during NASA/JPL AIRSAR PACRIM-II experiment in 2000.