Nonlinear filtering approach to 3-d gray-scale image interpolation

William E. Higgins, Christopher J. Orlick, Brian E. Ledell

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Three-dimensional (3-D) images are now common in radiology. A 3-D image is formed by stacking a contiguous sequence of two-dimensional cross-sectional images, or slices. Typically, the spacing between known slices is greater than the spacing between known points on a slice. Many visualization and image-analysis tasks, however, require the 3-D image to have equal sample spacing in all directions. To meet this requirement, one applies an interpolation technique to the known 3D image to generate a new uniformly sampled 3-D image. We propose a nonlinear-ftlter-based approach to gray-scale interpolation of 3-D images. The method, referred to as column-fitting interpolation, is reminiscent of the maximum-homogeneity filter used for image enhancement. We also draw upon the paradigm of relaxation labeling to devise an improved column-fitting interpolator. Both methods are typically more effecthe than traditional gray-scale interpolation techniques.

Original languageEnglish (US)
Pages (from-to)580-587
Number of pages8
JournalIEEE transactions on medical imaging
Issue number4
StatePublished - 1996

All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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