Filtered multiple observation image superposition

When an observation satellite scans the ground object, the images of the object are taken at different times from different angles because of swing of the observation orbit. Based on the principle of computed tomography and considering the properties of multiple observation, this paper presents a new approach, filtered multiple observation image superposition, to improve the spatial resolution of remotely sensed imagery. In this method, first, all of the lower spatial resolution images are expanded into the same size images as some expected higher spatial resolution image by interpolation. Second, every expanded image is enhanced by iterative unsharp masking to increase the high frequency components. Finally, all of enhanced images are superimposed into one higher resolution image by weighted average. The validity of this method is examined by error analysis and comparison