Image fusion is a process of blending the complementary as well as the common features of a set of images, to generate a resultant image with superior information content in terms of subjective as well as objective analysis point of view. Especially in the case of remotely sensed panchromatic and multispectral images its play a vital role to help subjective and objective analysis. Many algorithms and software tools have been developed for fusing panchromatic and multispectral datasets. Also, a number of methods have been proposed and developed for the comparative evaluation of fusion results. So most of the attempts focused on the change detection which had a few limitations. Thus a trail is made to detect, discover and reveal the boundary of satellite images (Raster and spatial vector data) using a novel approach for easy detection of boundary for classifying environmental changes in this paper. In this study, methods that evaluate fusion quality are tested for different images and test sites and the analysis shows that in most cases the tested methods performs well. © 2015 IJED (CESER Publications).