Improving the dynamic range of real-time X-ray imaging systems via Bayesian fusion

The performance and reliability of detecting flaws using X-ray techniques are largely conditioned by the dynamic range of the real-time X-ray imaging systems. This paper proposes a software solution to the problem of dynamic range improvement. The idea is to acquire two images of the same object under two different acquisition conditions, and to integrate these two images in order to obtain a more accurate range measurement of signal levels. To do this, a data fusion technique is developed that is based on the Bayesian theory. The Bayesian fusion method is illustrated with the aid of both simulations and examples on real images. The study demonstrates the possibility of improving significantly the dynamic range of real-time X-ray imaging systems using data fusion techniques.