The Principal Component Analysis (PCA) image fusion method has been used widely in recent years. However, without considering the effects of noise on the fusion image, its application is only limited to the fusion region. The Minimum Noise Fraction (MNF) transform is a self-contained component analysis method which considers the effects of noise on the fusion image. This technique is employed in such fields as the determination of the inherent dimensionality of image data and segregation of noise in the data; nevertheless, it is not applied to image fusion nowadays. Therefore, in view of the defectiveness of the PCA image fusion method and the superiority of the MNF transformation, the authors put forward a new MNF transform Remote Sensing fusion method in which both IKONOS multi-spectral image and panchromatic image are used. Visual and quantitative comparison demonstrates that this technique is better than other fusion methods.