Fusion of multispectral images is a major research problem in terms of surveillance, remote sensing, industrial automation, medical and defense applications. The main reason behind multispectral image fusion is that using single channel images does not meet requirements of classification, segmentation and related tasks of remote sensing applications. Therefore, a new solution is needed to combine multispectral images to get more accurate and good visualized image as well as preserving the important details behind them. With this purpose, we have a proposed a new image fusion technique by adopting the Common Vector Approach concept. Upon examining the results, one can observe that using the CVA method for image fusion promises good results when compared with Principal Component Analysis and Singular Value Decomposition.