The image change detection is been used in various applications like map updating, building change detection, disaster assessment, military application etc. In recent years image matching algorithm from computer vision have been introduced and used in satellite imagery. One of the important application of image change detection such as building change detection is discuss in this paper. When we are dealing with building change due to different imaging conditions 2D information obtain for different dates is not sufficient. It has been become difficult to distinguish the building changes from various man made construction such as roads and bridges due to similarity. So for to obtain the 3D building changes, stereo imagery is of importance. Therefore Digital Surface Model(DSM) and stereo imagery is used for building change detection. To detect the similarity information between two original images the Kullback Leibler Divergence(KLD) is preferred. Whereas Dempster Shafer Fusion theory (DS fusion) is used to combine the result of DSM and K L divergence , in order to improve accuracy. Image change detection can be used in both rural and urban area, image obtain from digital camera ,satellite, Google earth, USGS etc. Detecting and monitoring urban area changes are of great relevance for city planning, environmental monitoring. In this we have shown a example of image change detection. Change detection by information measure using radio metric information at the level of pixel is not sufficient to discriminate the ground structure. So object based or structural based image description are used to resolve the problem of radio metric information. If resolution of image is decreases than transform produce a non-linear temporal behavior which cannot be capture by linear transform change detection method.