Multisensor fusion of satellite images for urban information extraction using pseudo-Wigner distribution

Abstract A new algorithm has been proposed to fuse high-resolution panchromatic image with a low-resolution multispectral image of World View-2, based on pseudo-Wigner distribution (PWD). Spatial-frequency method, particularly PWD, provides pixel-wise analysis, shift invariant as well as characterization of local spectral properties of nonstationary image, which is indispensable for image fusion. The input images are re-sampled using nearest neighbor (NN), bicubic spline (BCS), and cubic convolution (CC). The comparison of performance of the proposed method and the discrete wavelet transform (DWT) has been evaluated using root mean square error, peak signal-to-noise ratio, correlation coefficient index. It has been found that PWD fusion technique outperforms DWT fusion technique using average as well as maximum selection rule, both quantitatively and qualitatively. All three resampling methods—the NN, the BCS, and the CC—do not have any significant effect on the final visual appearance of the fused images.