Contourlet-based multispectral image fusion

Fusion of high spectral but low spatial resolution multispectral and low spectral but high spatial resolution panchromatic satellite images is a very useful technique in various remote sensing applications, such as change detection. Recently, some studies showed that wavelet-based image fusion methods provide high quality spectral content of the fused image. However, most of wavelet-based methods have a spatial resolution of the fused result less than the Brovey, IHS, and PCA fusion methods. This is mainly because real wavelet transform cannot efficiently represent the singularity of linear/curved contents. In this paper, we introduce a new method based on the contourlet transform which represents edges better than real wavelets. Since edges play a fundamental role in image understanding, one good way to enhance spatial resolution is to enhance the edges. Here, we proposed an automatic threshold for discarding weak edges of panchromatic satellite images and strong edges were then fused in multi-spectral images. We evaluated the proposed approach on IRS satellite images and gave the comparison among the results obtained from the proposed method, the real wavelet transform, and the IHS method.