Image fusion using the curvelet transform: Comparative study applied to urban and peri urban areas of Algiers region (Algeria)

The 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 applications of remote sensing. In this paper, we describe approximate digital implementations of two new mathematical transforms, namely, the ridgelet transform and the curvelet transform, curvelet transform use the ridgelet transform as a component step, and implements curvelet subbands using a filter bank of a trous wavelet filters. Recently, some studies showed that wavelet-based image fusion method provides high quality of the 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. In this paper, we introduce a new method based on the curvelet transform which represents edges better than wavelets, Since edges play a fundamental role in image understanding, one good way to enhance spatial resolution is to enhance the edges. In order to validate the theoretical analysis, the performance of this method is evaluated by experimentation over images of the region (Algeria) from SPOT satellite (panchromatic and multispectral images).