Multi-scale Bayesian reconstruction of compressive X-ray image

Published

Conference Paper

© 2015 IEEE. 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.

Full Text

Duke Authors

Cited Authors

  • Huang, J; Yuan, X; Calderbank, R

Published Date

  • January 1, 2015

Published In

Volume / Issue

  • 2015-August /

Start / End Page

  • 1618 - 1622

International Standard Serial Number (ISSN)

  • 1520-6149

International Standard Book Number 13 (ISBN-13)

  • 9781467369978

Digital Object Identifier (DOI)

  • 10.1109/ICASSP.2015.7178244

Citation Source

  • Scopus