Abstract: A hypercomplex principle component weighted approach to multispectral and panchromatic images fusions is presented.Each pixel of a panchromatic image is firstly transformed into a vector.Such a vectorial panchromatic image and the multispectral images represented by RGB are then described by hypercomplex matrices respectively.Since those hypercomplex matrices can take the vectorial property of RGB components into account,the proposed approach can avoid the color distortion of the fused image happening in the IHS and PCA fusion approaches.The hypercomplex singular value decomposition approach is applied to the hypercomplex matrices of the vectorial panchromatic and multispectral images.By means of the principle component analysis of the hypercomplex singular values of two matrices,a method for fusing two images is obtained by weighting the eigenvector corresponding to the largest eigenvalue.Both the analysis and simulation results show that there is not the distortion of visible spectrums in the image fused by the proposed method.The evaluation results from the various methods representing the state of the art ones also show that the fusion results of the presented approach are better than those of the IHS,PCA and wavelet-based methods.