Improved cubic convolution for two dimensional image reconstruction

Research output: Contribution to conferencePaper

8 Scopus citations

Abstract

This paper describes improved piecewise cubic convolution for two-dimensional image reconstruction. Piecewise cubic convolution is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional approach is sub-optimal for the usual case of non-separable scenes and systems. The improved approach implements the most general two-dimensional, non-separable, piecewise cubic interpolator with constraints for symmetry, continuity, and smoothness.

Original languageEnglish (US)
Pages1775-1778
Number of pages4
StatePublished - 2001
Event2001 IEEE Nuclear Science Symposium Conference Record - San Diego, CA, United States
Duration: Nov 4 2001Nov 10 2001

Conference

Conference2001 IEEE Nuclear Science Symposium Conference Record
CountryUnited States
CitySan Diego, CA
Period11/4/0111/10/01

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Industrial and Manufacturing Engineering

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    Reichenbach, S. E., & Geng, F. (2001). Improved cubic convolution for two dimensional image reconstruction. 1775-1778. Paper presented at 2001 IEEE Nuclear Science Symposium Conference Record, San Diego, CA, United States.