Adaptive registration of remote sensing images using supervised learning

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strategy. During a training phase the system learns to recognize regions in an image suited for
registration. It also learns the relationship between image characteristics and registration
performance for a set of different registration algorithms. This enables intelligent selection of
an appropriate registration algorithm for each region in the image, while regions unsuited for
registration can be discarded. The approach is intended for co-registration of sequences of images acquired from identical or similar earth observation sensors. It has been tested for such sequences from different types of sensors, both optical and radar, with varying resolution. For images with moderate differences in content the registration accuracy is in general good with an RMS error of one pixel or less.