With the new trend of smaller missions in which sensors will be carried on separate platforms, the amount of remote sensing data to be combined will increase tremendously, and will require fast and automatic image registration and fusion. Image registration techniques will help develop 'ready to use' global datasets from multi-instrument/multi-platform/multi-temporal observations, while image fusion will provide new image products summarizing some basic understanding of the original data. These methods will find applications in numerous domains such as Earth science data analysis, map updating, and space exploration. Our work on image registration and fusion focuses on the speed of such methods and on their ability to handle multi-sensor data. These two requirements brought us to the utilization of multi-resolution wavelet transforms to perform such tasks. Our registration algorithm utilizes a wavelet-based multi-resolution search to determine the best transformation between two or more images to be registered. As of now, the algorithm searches for rotation, translation or a composition of both. This algorithm has been tested successfully on uni-sensor images -- landsat-thematic mapper (TM), advanced very high resolution radiometer (AVHRR), and geostationary operational environmental satellite (GOES) data, as well as multi-sensor data such as modis airborne simulator (MAS) with landsat-TM data. The second step in the combination of the data deals with the fusion of the data. This fusion can be considered at two levels; either the fusion occurs after registration of the original data and before any further analysis, or each individual dataset is analyzed independently and then a composite image is created. Both approaches may be considered utilizing a wavelet-based approach. Some preliminary results on image fusion are presented.