Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-senor/multi-spectral images has become a very important issue. A wide range of registration techniques has been developed for many different types of applications and data. Given the diversity of the data, it is unlikely that a single registration scheme will work satisfactorily for all different applications. A possible solution is to integrate multiple registration algorithms into a rule-based artificial intelligence system so that appropriate methods for any given set of multisensor data can be automatically selected. The first step in the development of such an expert system for remote sensing application would be to obtain a better understanding and characterization of the various existing techniques for image registration. This is the main objective of this paper as we present a comparative study of some recent image registration methods. We emphasize in particular techniques for multisensor image data, and a brief discussion of each of the techniques is given. This comprehensive study will enable the user to select algorithms that work best for his/here particular application domain.