Abstract:
A novel multi-scale dictionary based Bayesian reconstruction algorithm is proposed for compressive X-ray imaging, which encodes the material's spectrum by Poisson measurements. Inspired by recently developed compressive X-ray imaging systems [1], this work aims to recover the material's spectrum from the compressive coded image by leveraging a reference spectrum library. Instead of directly using the huge and redundant library as a dictionary, which is cumbersome in computation and difficult for selecting those active dictionary atoms, a multi-scale tree structured dictionary is refined from the spectrum library, and following this a Bayesian reconstruction algorithm is developed. Experimental results on real data demonstrate superior performance in comparison with traditional methods.
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