There is two important things in remote sensing satellite image fusion. They are preservation of spectral information and enhancement of spatial resolution. Remote sensing satellites like Quick bird and IKONOS provided only low-spatial-resolution multispectral (MS) images and high spatial- resolution panchromatic (PAN) images. It is very difficult to obtain high resolution multispectral images because of technical limitations of satellite sensors. So Image fusion is very important. The image fusion method is called Pan sharpening because a MS image is sharpened by injection of spatial details extracted from a PAN image. PAN sharpening algorithms are general component substitution methods like IHS, PCA etc. But they are having some draw backs in producing a good fused image. So here the latest technique New Adaptive Component Substitution Based Satellite Image Fusion by Using Partial Replacement is used. This method is having greater fusion quality and also this algorithm is suited to work with different sensors. In this project the PAN sharpening is done using Component substitution and partial replacement. Also the fused image by the proposed method is compared to another fused image by IHS Pan sharpening Method. The quality of the PAN Sharpening method using Component substitution fake taschen kaufen and Partial replacement is verified compared with IHS Pan Sharpening using the parameter Quality with No reference (QNR).