A Fourier Transform-based Approach to Fusion High Spatial Resolution Remote Sensing Images

The modern remote sensing imaging sensors, like those in the IKONOS and QuickBird satellites, are capable of generating panchromatic images with one meter spatial resolution and multispectral images with good spectral information. The principal objective of fusion in remote sensing is to obtain high-resolution multispectral images that can combine the spectral characteristic of the low-resolution multispectral images with the spatial information of the high-resolution panchromatic images. Traditional fusion methods, such as IHS, PCA and Brovey, can reach good spatial resolution results, but often cause spectral distortion problems. In the literature, it is possible to find some image fusion methods using frequency domain processing, like wavelet-based fusion methods. Although they preserve good spectral information, their spatial visual effects are not satisfactory. IHS fusion method enhanced by Fourier transform presents good spectral and spatial resolution results, but limits the number of spectral bands used in the fusion process to three. In this paper, a method based on Fourier transform is proposed in order to obtain good spatial and spectral resolutions, without limiting the number of bands. In order to compare the spatial and spectral effects of this new method with those of IHS, IHS enhanced by Fourier transform and wavelet-based methods, IKONOS panchromatic and multispectral images were used as the test data. Quantitative measurements such as correlation coefficient, discrepancy and Mean Structural Similarity index were applied to evaluate the quality of the fused images. The results have shown that the new method can keep almost the same spatial resolution as the panchromatic images, and its spectral effect is well preserved.