Model-based sensor fusion for aviation

We describe a sensor fusion algorithm based on a set of simple assumptions about the relationship among the sensors. Under these assumptions we estimate the common signal in each sensor, and the optimal fusion is then approximated by a weighted sum of the common component in each sensor output at each pixel. We then examine a variety of techniques to map the sensor signals onto perceptual dimensions (e.g., color), such that the human operator can beneet from the enhanced fused image, and simultaneously, be able to identify the source of the information. We examine several color mapping schemes.