The entropy weighted non-uniform scanning algorithm for diffraction tomography

Yu Li Sun, Jin Xu Tao, Hao Chen, Cong Gui Liu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This paper studies diffraction tomography based on Fourier diffraction projection theorem. By the observation of frequency domain projecting image, one can find that projection in frequency domain is not uniformly distributed when the spatial domain scanning angle is equispaced. This results in loss of information. We analyze the conditions under which the information lost most. Then, we define the information entropy of each scanning and propose a non-uniform scanning algorithm to maximize the amount of information under conditions of a fixed number of sampling points and scanning angles. The algorithm has five different kinds of the weighting vectors based on different weighting programs. The simulation result supports our hypotheses and indicates that the algorithm proposed in this paper can obviously improve the reconstruction quality.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalScience China Information Sciences
Volume58
Issue number6
DOIs
StatePublished - 18 Jun 2015

Keywords

  • diffraction tomography
  • entropy
  • Fourier diffraction projection theorem
  • total variation

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