Image reconstruction with two-dimensional piecewise polynomial convolution

Research output: Contribution to journalConference article

3 Scopus citations


This paper describes two-dimensional, non-separable, piecewise polynomial convolution for image reconstruction. We investigate a two-parameter kernel with support [-2,2]×[-2,2] and constrained for smooth reconstruction. Performance reconstructing a sampled random Markov field is superior to the traditional one-dimensional cubic convolution algorithm.

Original languageEnglish (US)
Pages (from-to)3237-3240
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication statusPublished - Jan 1 1999
EventProceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99) - Phoenix, AZ, USA
Duration: Mar 15 1999Mar 19 1999


ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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