Most image coding algorithms, like the P X 64 and MPEG-1 standards, use locally derived estimates of object motion to form a prediction of the current frame. But camera motion, such as zooms and pans, which systemically affect the entire frame, is seldom handled efficiently. In this paper, we study the modeling, estimation and compensation of global motion caused by camera zooms and pans, we model the global motion in each frame with just two parameters: a scalar zoom factor and a 2D pan vector. Parameter estimation minimizes the squared prediction error of either the difference frame or the optical flow field. The estimated parameters are then used to construct a zoom/pan compensated prediction of the current frame, upon which some local motion compensation algorithm can then be applied to model object motion. Simulations suggest that these two global motion estimation algorithms are robust and accurate, and that global motion compensation provides a better prediction of the current frame with a potentially large reduction of motion side information.