Multisensor data fusion technique has been widely used in remote sensing image processing. A major problem in using remote sensing multispectral images is the low spatial resolution. In order to improve spatial resolution of the multispectral images

a multiresolution image fusion method based on the normalized correlation moment is proposed in this paper. After 2 D wavelet transform the normalized correlation moment is defined by means of statistic first order and second order moment of those wavelet coefficients with high frequency component under different resolutions. By using the local correlation moment as measure of feature selection

the new method carries out multiresolution images fusion. And the fused images include more useful information for further application. Experiments are conducted on Landsat TM and SPOT data. Computer simulations show that the fused images obtain better results in terms of both preserving spectral information and improving spatial resolution of the multispectral images

and are rather used to many aspects of remote sensing image processing such as target recognition

ground materials classification

etc.