In this paper, fusion of multispectral images for visualization is aimed at, based on the projection of the scatter-diagrams onto a one-dimensional space. Linear as well as nonlinear projection techniques are used. In contrast, with existing mapping techniques, which work globally, a local mapping technique, are constructed. In this technique, the images are subdivided into blocks, where each block of pixels is visualized through a different map. Then, for each pixel, weighting the maps of the surrounding blocks using a Euclidean distance measure creates a locally adapted map. A linear local mapping, based on local PCA and a nonlinear local mapping, based on Kohonen's SOM map are generated and compared to the global procedures. Experiments are conducted on multispectral LANDSAT imagery.