Data redundancy and reduced-scan reconstruction in reflectivity tomography

Xiaochuan Pan, Yu Zou, Mark A. Anastasio

Research output: Contribution to journalArticlepeer-review


In reflectivity tomography, conventional reconstruction approaches require that measurements be acquired at view angles that span a full angular range of 2π. It is often, however, advantageous to reduce the angular range over which measurements are acquired, which can, for example, minimize artifacts due to movements of the imaged object. Moreover, in certain situations it may not be experimentally possible to collect data over a 2π angular range. In this work, we investigate the problem of reconstructing images from reduced-scan data in reflectivity tomography. By exploiting symmetries in the data function of reflectivity tomography, we heuristically demonstrate that an image function can be uniquely specified by reduced-scan data that correspond to measurements taken over an angular interval (possibly disjoint) that spans at least π radians. We also identify sufficient conditions that permit for a stable reconstruction of image boundaries from reduced-scan data. Numerical results in computer-simulation studies indicate that images can be reconstructed accurately from reduced-scan data.

Original languageEnglish (US)
Pages (from-to)784-795
Number of pages12
JournalIEEE Transactions on Image Processing
Issue number7
StatePublished - Jul 2003
Externally publishedYes


  • Data redundancy
  • Image reconstruction
  • Reduced scan
  • Reflectivity tomography

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Software
  • Electrical and Electronic Engineering
  • Theoretical Computer Science


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