Panchromatic and Multispectral Image Fusion Based on Maximization of Both Spectral and Spatial Similarities

The panchromatic (PAN) sharpening of multispectral (MS) bands can be performed by fusing the PAN and MS images. Measuring similarity criterion computed among input images is one way to synthesize MS images in higher resolution based on either spectral or spatial domains. However, a few methods consider both spectral and spatial similarities. In this paper, the fusion between PAN and MS images is performed by engaging both similarities. We use the spectral histogram, recently introduced to characterize the spectral information of an image in different frequency ranges, as the spectral similarity criterion. This similarity suggests considering a statistical similarity measure between two spectral histograms of two images. Furthermore, we use the fourth-order correlation coefficient as a spatial similarity criterion instead of correlation coefficient. Meanwhile, in the decision level of fusion process, a proper threshold should be selected to determine whether the details should be injected or not. There is no reference to choose it in general cases, and this threshold is calculated for each set of input images separately and is based on intersecting two similarity curves. We do this by first calculating the spatial and spectral similarity criteria for some specific threshold values and then fit two similarity curves on these sample points by the spline interpolation method. Then, after decomposing input images using the nonsubsampled contourlet transform, we inject the PAN details into the MS details considering the selected threshold. The experimental results obtained by applying the proposed image fusion method indicate some improvements in the fusion performance.