Abstract

Both image registration and fusion are essential steps to produce high-resolution multispectral images in remote sensing. Traditionally, they are viewed as two independent processes. As a result, the registration errors ignored in the fusion process can significantly affect the fusion quality. In this context, an iterative optimization approach, which jointly considers the registration and fusion processes, is proposed for panchromatic (PAN) and multispectral (MS) images. Given a registration method and a fusion method, the joint optimization process is described as finding the optimal registration parameters to gain the optimal fusion performance. In our approach, the downhill simplex algorithm is adopted to refine the registration parameters iteratively. Experiments on a set of PAN and MS images of ZY-3 and GeoEye-1 show that the proposed approach outperforms several competing ones in terms of registration accuracy and fusion quality.

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